How can I pair socks from a pile efficiently

Question

Yesterday I was pairing the socks from the clean laundry and figured out the way I was doing it is not very efficient  I was doing a naive search nbsp     picking one sock and  iterating  the pile in order to find its pair  This requires iterating over n 2   n 4   n2 8 socks on average   As a computer scientist I was thinking what I could do  Sorting  according to size color      of course came to mind to achieve an O NlogN  solution   Hashing or other not-in-place solutions are not an option  because I am not able to duplicate my socks  though it could be nice if I could    So  the question is basically   Given a pile of n pairs of socks  containing 2n elements  assume each sock has exactly one matching pair   what is the best way to pair them up efficiently with up to logarithmic extra space   I believe I can remember that amount of info if needed    I will appreciate an answer that addresses the following aspects    A general theoretical solution for a huge number of socks  The actual number of socks is not that large  I don t believe my spouse and I have more than 30 pairs   And it is fairly easy to distinguish between my socks and hers  can this be used as well   Is it equivalent to the element distinctness problem

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When I sort socks  I do an approximate radix sort  dropping socks near other socks of the same colour pattern type  Except in the case when I can see an exact match at near the location I m about to drop the sock I extract the pair at that point   Almost all the other algorithms  including the top scoring answer by usr  sort  then remove pairs  I find that  as a human  it is better to minimize the number of socks being considered at one time    I do this by    Picking a distinctive sock  whatever catches my eye first in the pile   Starting a radix sort from that conceptual location by pulling socks from the pile based on similarity to that one   Place the new sock near into the current pile  with a distance based on how different it is  If you find yourself putting the sock on top of another because it is identical  form the pair there  and remove them  This means that future comparisons take less effort to find the correct place    This takes advantage of the human ability to fuzzy-match in O 1  time  which is somewhat equivalent to the establishment of a hash-map on a computing device   By pulling the distinctive socks first  you leave space to  zoom  in on the features which are less distinctive  to begin with   After eliminating the fluro coloured  the socks with stripes  and the three pairs of long socks  you might end up with mostly white socks roughly sorted by how worn they are   At some point  the differences between socks are small enough that other people won t notice the difference  and any further matching effort is not needed

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Here s an Omega n log n  lower bound in comparison based model   The only valid operation is comparing two socks    Suppose that you know that your 2n socks are arranged this way   p1 p2 p3     pn pf 1  pf 2      pf n   where f is an unknown permutation of the set  1 2     n   Knowing this cannot make the problem harder  There are n  possible outputs  matchings between first and second half   which means you need log n     Omega n log n  comparisons  This is obtainable by sorting   Since you are interested in connections to element distinctness problem  proving the Omega n log n  bound for element distinctness is harder  because the output is binary yes no  Here  the output has to be a matching and the number of possible outputs suffices to get a decent bound  However  there s a variant connected to element distinctness  Suppose you are given 2n socks and wonder if they can be uniquely paired  You can get a reduction from ED by sending  a1  a2       an  to  a1  a1  a2  a2       an  an    Parenthetically  the proof of hardness of ED is very interesting  via topology    I think that there should be an Omega n2  bound for the original problem if you allow equality tests only  My intuition is  Consider a graph where you add an edge after a test  and argue that if the graph is not dense the output is not uniquely determined

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Consider a hash-table of  size   N    If we assume normal distribution  then the estimated number of  insertions   to have atleast one sock mapped to one bucket is NlogN   ie  all buckets are full    I had derived this as a part of another puzzle but I would be happy to be proven wrong   Here s my blog article on the same     Let  N  correspond to an approximate upper-bound on the number of  number of unique colors pattern of socks that you have   Once you have a collision a k a    a match  simply remove that pair of socks    Repeat the same experiment with the next batch of NlogN socks   The beauty of it is that you could be making NlogN parallel comparisons collision-resolution  because of the way the human mind works    -

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List lt Sock gt  UnSearchedSocks   getAllSocks    List lt Sock gt  UnMatchedSocks   new list lt Sock gt     List lt PairOfSocks gt  PairedSocks   new list lt PairOfSocks gt      foreach  Sock newSock in UnsearchedSocks      Sock MatchedSock   null    foreach Sock UnmatchedSock in UnmatchedSocks          if  UnmatchedSock isPairOf newSock               MatchedSock   UnmatchedSock        break              if  MatchedSock    null          UnmatchedSocks remove MatchedSock       PairedSocks Add new PairOfSocks MatchedSock  NewSock          else         UnmatchedSocks Add NewSock

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My proposed solution assumes that all socks are identical in details  except by color  If there are more details to defer between socks  these details can be used to define different types of socks instead of colors in my example     Given that we have a pile of socks  a sock can come in three colors  Blue  red  or green   Then we can create a parallel worker for each color  it has its own list to fill corresponding colors   At time i   Blue  read  Pile i       If Blue  then Blue Count      B TRUE    sync  Red   read  Pile i 1     If Red   then Red Count       R TRUE    sync  Green read  Pile  i 2    If Green then Green Count     G TRUE    sync   With synchronization process   Sync i   i    If R is TRUE      i       If G is TRUE          i     This requires an initialization   Init   If Pile 0     Blue      If      Pile 0    Red     Red Count       Else if Pile 0    Green   Green Count    If Pile 1     Red      If Pile 0    Green   Green Count     Where  Best Case  B  R  G  B  R  G      B  R  G  Worst Case  B  B  B      B  Time Worst-Case    C   n   O n   Time Best-Case    C    n k    O n k   n  number of sock pairs k  number of colors C  sync overhead

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If the  move  operation is fairly expensive  and the  compare  operation is cheap  and you need to move the whole set anyway  into a buffer where search is much faster than in original storage    just integrate sorting into the obligatory move   I found integrating the process of sorting into hanging to dry makes it a breeze  I need to pick up each sock anyway  and hang it  move  and it costs me about nothing to hang it in a specific place on the strings  Now just not to force search of the whole buffer  the strings  I choose to place socks by color shade  Darker left  brighter right  more colorful front etc  Now before I hang each sock  I look in its  right vicinity  if a matching one is there already - this limits  scan  to 2-3 other socks - and if it is  I hang the other one right next to it  Then I roll them into pairs while removing from the strings  when dry   Now this may not seem all that different from  forming piles by color  suggested by top answers but first  by not picking discrete piles but ranges  I have no problem classifying whether  purple  goes to  red  or  blue  pile  it just goes between  And then by integrating two operations  hang to dry and sort  the overhead of sorting while hanging is like 10  of what separate sorting would be

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I ve finished pairing my socks just right now  and I found that the best way to do it is the following    Choose one of the socks and put it away  create a  bucket  for that pair  If the next one is the pair of the previous one  then put it to the existing bucket  otherwise create a new one    In the worst case it means that you will have n 2 different buckets  and you will have n-2 determinations about that which bucket contains the pair of the current sock  Obviously  this algorithm works well if you have just a few pairs  I did it with 12 pairs   It is not so scientific  but it works well

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Sorting solutions have been proposed  but sorting is a little too much  We don t need order  we just need equality groups   So hashing would be enough  and faster     For each color of socks  form a pile  Iterate over all socks in your input basket and distribute them onto the color piles  Iterate over each pile and distribute it by some other metric  e g  pattern  into the second set of piles Recursively apply this scheme until you have distributed all socks onto very small piles that you can visually process immediately   This kind of recursive hash partitioning is actually being done by SQL Server when it needs to hash join or hash aggregate over huge data sets  It distributes its build input stream into many partitions which are independent  This scheme scales to arbitrary amounts of data and multiple CPUs linearly   You don t need recursive partitioning if you can find a distribution key  hash key  that provides enough buckets that each bucket is small enough to be processed very quickly  Unfortunately  I don t think socks have such a property   If each sock had an integer called  PairID  one could easily distribute them into 10 buckets according to PairID   10  the last digit    The best real-world partitioning I can think of is creating a rectangle of piles  one dimension is color  the other is the pattern  Why a rectangle  Because we need O 1  random-access to piles   A 3D cuboid would also work  but that is not very practical      Update   What about parallelism  Can multiple humans match the socks faster    The simplest parallelization strategy is to have multiple workers take from the input basket and put the socks onto the piles  This only scales up so much - imagine 100 people fighting over 10 piles  The synchronization costs  manifesting themselves as hand-collisions and human communication  destroy efficiency and speed-up  see the Universal Scalability Law    Is this prone to deadlocks  No  because each worker only needs to access one pile at a time  With just one  lock  there cannot be a deadlock  Livelocks might be possible depending on how the humans coordinate access to piles  They might just use random backoff like network cards do that on a physical level to determine what card can exclusively access the network wire  If it works for NICs  it should work for humans as well  It scales nearly indefinitely if each worker has its own set of piles  Workers can then take big chunks of socks from the input basket  very little contention as they are doing it rarely  and they do not need to synchronise when distributing the socks at all  because they have thread-local piles   At the end  all workers need to union their pile-sets  I believe that can be done in O log  worker count   piles per worker   if the workers form an aggregation tree    What about the element distinctness problem  As the article states  the element distinctness problem can be solved in O N   This is the same for the socks problem  also O N   if you need only one distribution step  I proposed multiple steps only because humans are bad at calculations - one step is enough if you distribute on md5 color  length  pattern        i e  a perfect hash of all attributes     Clearly  one cannot go faster than O N   so we have reached the optimal lower bound   Although the outputs are not exactly the same  in one case  just a boolean  In the other case  the pairs of socks   the asymptotic complexities are the same

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What about doing some preprocessing  I would stitch a mark or id number in every sock in a way that every pair has the same mark id number  This process might be done every time you buy a new pair of socks  Then  you could do a radix sort to get O n  total cost  Find a place for every mark id number and just pick all the socks one by one and put them into the correct place

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Real-world approach   As rapidly as possible  remove socks from the unsorted pile one at a time and place in piles in front of you  The piles should be arranged somewhat space-efficiently  with all socks pointing the same direction  the number of piles is limited by the distance you can easily reach  The selection of a pile on which to put a sock should be -- as rapidly as possible -- by putting a sock on a pile of apparently like socks  the occasional type I  putting a sock on a pile it doesn t belong to  or type II  putting a sock in its own pile when there s an existing pile of like socks  error can be tolerated -- the most important consideration is speed   Once all the socks are in piles  rapidly go through the multi-sock piles creating pairs and removing them  these are heading for the drawer   If there are non-matching socks in the pile  re-pile them to their best  within the as-fast-as-possible constraint  pile  When all the multi-sock piles have been processed  match up remaining pairable socks that weren t paired due to type II errors  Whoosh  you re done -- and I have a lot of socks and don t wash them until a large fraction are dirty  Another practical note  I flip the top of one of a pair of socks down over the other  taking advantage of their elastic properties  so they stay together while being transported to the drawer and while in the drawer

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From your question it is clear you don t have much actual experience with laundry     You need an algorithm that works well with a small number of non-pairable socks   The answers till now don t make good use of our human pattern recognition capabilities  The game of Set provides a clue of how to do this well  put all socks in a two-dimensional space so you can both recognize them well and easily reach them with your hands  This limits you to an area of about 120   80 cm or so  From there select the pairs you recognize and remove them  Put extra socks in the free space and repeat  If you wash for people with easily recognizable socks  small kids come to mind   you can do a radix sort by selecting those socks first  This algorithm works well only when the  number of single socks is low

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Case 1  All socks are identical  this is what I do in real life by the way     Pick any two of them to make a pair  Constant time   Case 2  There are a constant number of combinations  ownership  color  size  texture  etc     Use radix sort  This is only linear time since comparison is not required   Case 3  The number of combinations is not known in advance  general case    We have to do comparison to check whether two socks come in pair  Pick one of the O n log n  comparison-based sorting algorithms   However in real life when the number of socks is relatively small  constant   these theoretically optimal algorithms wouldn t work well  It might take even more time than sequential search  which theoretically requires quadratic time

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I have taken simple steps to reduce my effort into a process taking O 1  time   By reducing my inputs to one of two types of socks  white socks for recreation  black socks for work   I only need to determine which of two socks I have in hand   Technically  since they are never washed together  I have reduced the process to O 0  time    Some upfront effort is required to find desirable socks  and to purchase in sufficient quantity as to eliminate need for your existing socks  As I d done this before my need for black socks  my effort was minimal  but mileage may vary   Such an upfront effort has been seen many times in very popular and effective code  Examples include  DEFINE ing pi to several decimals  other examples exist  but that s the one that comes to mind right now

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The theoretical limit is O n  because you need to touch each sock  unless some are already paired somehow    You can achieve O n  with radix sort  You just need to pick some attributes for the buckets     First you can choose  hers  mine  - split them into 2 piles  then use colors  can have any order for the colors  e g  alphabetically by color name  - split them into piles by color  remember to keep the initial order from step 1 for all socks in the same pile   then length of the sock  then texture         If you can pick a limited number of attributes  but enough attributes that can uniquely identify each pair  you should be done in O k   n   which is O n  if we can consider k is limited

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As a practical solution    Quickly make piles of easily distinguishable socks   Say by color  Quicksort every pile and use the length of the sock for comparison  As a human you can make a fairly quick decision which sock to use to partition that avoids worst case   You can see multiple socks in parallel  use that to your advantage   Stop sorting piles when they reached a threshold at which you are comfortable to find spot pairs and unpairable socks instantly   If you have 1000 socks  with 8 colors and an average distribution  you can make 4 piles of each 125 socks in c n time  With a threshold of 5 socks you can sort every pile in 6 runs   Counting 2 seconds to throw a sock on the right pile it will take you little under 4 hours    If you have just 60 socks  3 colors and 2 sort of socks  yours   your wife s  you can sort every pile of 10 socks in 1 runs  Again threshold   5    Counting 2 seconds it will take you 2 min    The initial bucket sorting will speed up your process  because it divides your n socks into k buckets in c n time so than you will only have to do c n log k  work   Not taking into account the threshold   So all in all you do about n c  1   log k   work  where c is the time to throw a sock on a pile   This approach will be favourable compared to any c x n   O 1  method roughly as long as log k   lt  x - 1     In computer science this can be helpful  We have a collection of n things  an order on them  length  and also an equivalence relation  extra information  for example the color of socks   The equivalence relation allows us to make a partition of the original collection  and in every equivalence class our order is still maintained  The mapping of a thing to it s equivalence class can be done in O 1   so only O n  is needed to assign each item to a class  Now we have used our extra information and can proceed in any manner to sort every class  The advantage is that the data sets are already significantly smaller   The method can also be nested  if we have multiple equivalence relations -  make colour piles  than within every pile partition on texture  than sort on length  Any equivalence relation that creates a partition with more than 2 elements that have about even size will bring a speed improvement over sorting  provided we can directly assign a sock to its pile   and the sorting can happen very quickly on smaller data sets

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We can use hashing to our leverage if you can abstract a single pair of socks as the key itself and its other pair as value    Make two imaginary sections behind you on the floor  one for you and another for your spouse   Take one from the pile of socks  Now place the socks on the floor  one by one  following the below rule    Identify the socks as yours or hers and look at the relevant section on the floor  If you can spot the pair on the floor pick it up and knot them up or clip them up or do whatever you would do after you find a pair and place it in a basket  remove it from the floor   Place it in the relevant section   Repeat 3 until all socks are over from the pile     Explanation   Hashing and Abstraction  Abstraction is a very powerful concept that has been used to improve user experience  UX   Examples of abstraction in real-life interactions with computers include    Folder icons used for navigation in a GUI  graphical user interface  to access an address instead of typing the actual address to navigate to a location  GUI sliders used to control various levels of volume  document scroll position  etc        Hashing or other not-in-place solutions are not an option because I am not able to duplicate my socks  though it could be nice if I could     I believe the asker was thinking of applying hashing such that the slot to which either pair of sock goes should be known before placing them   That s why I suggested abstracting a single sock that is placed on the floor as the hash key itself  hence there is no need to duplicate the socks    How to define our hash key   The below definition for our key would also work if there are more than one pair of similar socks  That is  let s say there are two pairs of black men socks PairA and PairB  and each sock is named PairA-L  PairA-R  PairB-L  PairB-R  So PairA-L can be paired with PairB-R  but PairA-L and PairB-L cannot be paired   Let say any sock can be uniqly identified by   Attribute Gender    Attribute Colour    Attribute Material    Attribute Type1    Attribute Type2    Attribute Left or Right   This is our first hash function  Let s use a short notation for this h1 G C M T1 T2 LR   h1 x  is not our location key   Another hash function eliminating the Left or Right attribute would be h2 G C M T1 T2   This second function h2 x  is our location key   for the space on the floor behind you     To locate the slot  use h2 G C M T1 T2   Once the slot is located then use h1 x  to check their hashes  If they don t match  you have a pair  Else throw the sock into the same slot    NOTE  Since we remove a pair once we find one  it s safe to assume that there would only be at a maximum one slot with a unique h2 x  or h1 x  value   In case we have each sock with exactly one matching pair then use h2 x  for finding the location and if no pair  a check is required  since it s safe to assume they are a pair   Why is it important to lay the socks on the floor  Let s consider a scenario where the socks are stacked over one another in a pile  worst case   This means we would have no other choice but to do a linear search to find a pair   Spreading them on the floor gives more visibility which improves the chance of spotting the matching sock  matching a hash key    When a sock was placed on the floor in step 3  our mind had subconsciously registered the location     - So in case  this location is available in our memory we can directly find the matching pair    - In case the location is not remembered  don t worry  then we can always revert back to linear search   Why is it important to remove the pair from the floor    Short-term human memory works best when it has fewer items to remember  Thus increasing the probability of us resorting to hashing to spot the pair   It will also reduce the number of items to be searched through when linear searching for the pair is being used    Analysis   Case 1  Worst case when Derpina cannot remember or spot the socks on the floor directly using the hashing technique  Derp does a linear search through the items on the floor  This is not worse than the iterating through the pile to find the pair    Upper bound for comparison  O n 2   Lower bound for comparison   n 2    when every other sock Derpina picks up is the pair of previous one    Case 2  Derp remembers each the location of every sock that he placed on the floor and each sock has exactly one pair    Upper bound for comparison  O n 2   Lower bound for comparison  O n 2      I am talking about comparison operations  picking the socks from the pile would necessarily be n number of operations  So a practical lower bound would be n iterations with n 2 comparisons   Speeding up things  To achieve a perfect score so Derp gets O n 2  comparisons  I would recommend Derpina to    spend more time with the socks to get familiarize with it  Yes  that means spending more time with Derp s socks too  Playing memory games like spot the pairs in a grid can improve short-term memory performance  which can be highly beneficial    Is this equivalent to the element distinctness problem   The method I suggested is one of the methods used to solve element distinctness problem where you place them in the hash table and do the comparison    Given your special case where there exists only one exact pair  it has become very much equivalent to the element distinct problem  Since we can even sort the socks and check adjacent socks for pairs  another solution for EDP     However  if there is a possibility of more than one pair that can exist for given sock then it deviates from EDP

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I hope I can contribute something new to this problem  I noticed that all of the answers neglect the fact that there are two points where you can perform preprocessing  without slowing down your overall laundry performance   Also  we don t need to assume a large number of socks  even for large families  Socks are taken out of the drawer and are worn  and then they are tossed in a place  maybe a bin  where they stay before being laundered  While I wouldn t call said bin a LIFO-Stack  I d say it is safe to assume that    people toss both of their socks roughly in the same area of the bin  the bin is not randomized at any point  and therefore  any subset taken from the top of this bin generally contains both socks of a pair    Since all washing machines I know about are limited in size  regardless of how many socks you have to wash   and the actual randomizing occurs in the washing machine  no matter how many socks we have  we always have small subsets which contain almost no singletons    Our two preprocessing stages are  putting the socks on the clothesline  and  Taking the socks from the clothesline   which we have to do  in order to get socks which are not only clean but also dry  As with washing machines  clotheslines are finite  and I assume that we have the whole part of the line where we put our socks in sight   Here s the algorithm for put socks on line     while  socks left in basket     take sock     if  cluster of similar socks is present        Add sock to cluster  if possible  next to the matching pair     else     Hang it somewhere on the line  this is now a new cluster of similar-looking socks          Leave enough space around this sock to add other socks later on         Don t waste your time moving socks around or looking for the best match  this all should be done in O n   which we would also need for just putting them on the line unsorted  The socks aren t paired yet  we only have several similarity clusters on the line  It s helpful that we have a limited set of socks here  as this helps us to create  good  clusters  for example  if there are only black socks in the set of socks  clustering by colours would not be the way to go   Here s the algorithm for take socks from line     while socks left on line     take next sock     if  matching pair visible on line or in basket       Take it as well  pair  em and put  em away    else      put the sock in the basket      I should point out that in order to improve the speed of the remaining steps  it is wise not to randomly pick the next sock  but to sequentially take sock after sock from each cluster  Both preprocessing steps don t take more time than just putting the socks on the line or in the basket  which we have to do no matter what  so this should greatly enhance the laundry performance   After this  it s easy to do the hash partitioning algorithm  Usually  about 75  of the socks are already paired  leaving me with a very small subset of socks  and this subset is already  somewhat  clustered  I don t introduce much entropy into my basket after the preprocessing steps   Another thing is that the remaining clusters tend to be small enough to be handled at once  so it is possible to take a whole cluster out of the basket   Here s the algorithm for sort remaining clusters     while clusters present in basket      Take out the cluster and spread it   Process it immediately   Leave remaining socks where they are     After that  there are only a few socks left  This is where I introduce previously unpaired socks into the system and process the remaining socks without any special algorithm - the remaining socks are very few and can be processed visually very fast   For all remaining socks  I assume that their counterparts are still unwashed and put them away for the next iteration  If you register a growth of unpaired socks over time  a  sock leak    you should check your bin - it might get randomized  do you have cats which sleep in there    I know that these algorithms take a lot of assumptions  a bin which acts as some sort of LIFO stack  a limited  normal washing machine  and a limited  normal clothesline - but this still works with very large numbers of socks   About parallelism  As long as you toss both socks into the same bin  you can easily parallelize all of those steps

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This is asking the wrong question  The right question to ask is  why am I spending time sorting socks  How much does it cost on yearly basis  when you value your free time for X monetary units of your choice   And more often than not  this is not just any free time  it s morning free time  which you could be spending in bed  or sipping your coffee  or leaving a bit early and not being caught in the traffic   It s often good to take a step back  and think a way around the problem   And there is a way   Find a sock you like  Take all relevant features into account  colour in different lighting conditions  overall quality and durability  comfort in different climatic conditions  and odour absorption  Also important is  they should not lose elasticity in storage  so natural fabrics are good  and they should be available in a plastic wrapping   It s better if there s no difference between left and right foot socks  but it s not critical  If socks are left-right symmetrical  finding a pair is O 1  operation  and sorting the socks is approximate O M  operation  where M is the number of places in your house  which you have littered with socks  ideally some small constant number   If you chose a fancy pair with different left and right sock  doing a full bucket sort to left and right foot buckets take O N M   where N is the number of socks and M is same as above  Somebody else can give the formula for average iterations of finding the first pair  but worst case for finding a pair with blind search is N 2 1  which becomes astronomically unlikely case for reasonable N  This can be sped up by using advanced image recognition algorithms and heuristics  when scanning the pile of unsorted socks with Mk1 Eyeball   So  an algorithm for achieving O 1  sock pairing efficiency  assuming symmetrical sock  is    You need to estimate how many pairs of socks you will need for the rest of your life  or perhaps until you retire and move to warmer climates with no need to wear socks ever again  If you are young  you could also estimate how long it takes before we ll all have sock-sorting robots in our homes  and the whole problem becomes irrelevant  You need to find out how you can order your selected sock in bulk  and how much it costs  and do they deliver  Order the socks  Get rid of your old socks    An alternative step 3 would involve comparing costs of buying the same amount of perhaps cheaper socks a few pairs at a time over the years and adding the cost of sorting socks  but take my word for it  buying in bulk is cheaper  Also  socks in storage increase in value at the rate of stock price inflation  which is more than you would get on many investments  Then again there is also storage cost  but socks really do not take much space on the top shelf of a closet   Problem solved  So  just get new socks  throw donate your old ones away  and live happily ever after knowing you are saving money and time every day for the rest of your life

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I thought about this very often during my PhD  in computer science   I came up with multiple solutions  depending on the ability to distinguish socks and thus find correct pairs as fast as possible   Suppose the cost of looking at socks and memorizing their distinctive patterns is negligible  e   Then the best solution is simply to throw all socks on a table  This involves those steps    Throw all socks on a table  1  and create a hashmap  pattern  position   e  While there are remaining socks  n 2     Pick up one random sock  1  Find position of corresponding sock  e  Retrieve sock  1  and store pair    This is indeed the fastest possibility and is executed in n   1   O n  complexity  But it supposes that you perfectly remember all patterns    In practice  this is not the case  and my personal experience is that you sometimes don t find the matching pair at first attempt    Throw all socks on a table  1  While there are remaining socks  n 2     Pick up one random sock  1  while it is not paired  1 P     Find sock with similar pattern Take sock and compare both  1  If ok  store pair     This now depends on our ability to find matching pairs  This is particularly true if you have dark grey pairs or white sports socks that often have very similar patterns  Let s admit that you have a probability of P of finding the corresponding sock  You ll need  on average  1 P tries before finding the corresponding sock to form a pair  The overall complexity is 1    n 2     1   1 P    O n    Both are linear in the number of socks and are very similar solutions  Let s slightly modify the problem and admit you have multiple pairs of similar socks in the set  and that it is easy to store multiple pairs of socks in one move  1 e   For K distinct patterns  you may implement    For each sock  n     Pick up one random sock  1  Put it on its pattern s cluster  For each cluster  K     Take cluster and store pairs of socks  1 e     The overall complexity becomes n K   O n   It is still linear  but choosing the correct algorithm may now greatly depend on the values of P and K  But one may object again that you may have difficulties to find  or create  cluster for each sock   Besides  you may also loose time by looking on websites what is the best algorithm and proposing your own solution

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Towards an efficient algorithm for pairing socks from a pile Preconditions  There must be at least one sock in the pile The table must be large enough to accommodate N 2 socks  worst case   where N is the total number of socks   Algorithm Try   Pick the first sock Put it down on the table Pick next sock  and look at it  may throw  no more socks in the pile    exception  Now scan the socks on the table  throws exception if there are no socks left on the table  Is there any match  a  yes   gt  remove the matching sock from the table b  no   gt   put the sock on the table  may throw  the table is not large enough  exception   Except   The table is not large enough        carefully mix all unpaired socks together  then resume operation          this operation will result in a new pile and an empty table  No socks left on the table        throw  the last unpairable sock   No socks left in the pile        exit laundry room   Finally   If there are still socks in the pile        goto 3  Known issues The algorithm will enter an infinite loop if there is no table around or there is not enough place on the table to accommodate at least one sock  Possible improvement Depending on the number of socks to be sorted  throughput could be increased by sorting the socks on the table  provided there s enough space  In order for this to work  an attribute is needed that has a unique value for each pair of socks  Such an attribute can be easily synthesized from the visual properties of the socks  Sort the socks on the table by said attribute  Let s call that attribute   colour   Arrange the socks in a row  and put darker coloured socks to the right  i e   push back    and lighter coloured socks to the left  i e   push front    For huge piles and especially previously unseen socks  attribute synthesis might require significant time  so throughput will apparently decrease  However  these attributes can be persisted in memory and reused  Some research is needed to evaluate the efficiency of this possible improvement  The following questions arise   What is the optimal number of socks to be paired using above improvement  For a given number of socks  how many iterations are needed before throughput increases  a  for the last iteration b  for all iterations overall  PoC in line with the MCVE guidelines   include  lt iostream gt   include  lt vector gt   include  lt string gt   include  lt time h gt   using namespace std   struct pileOfsocks       pileOfsocks int pairCount   42            elemCount pairCount lt  lt 1            srand time NULL            socks resize elemCount            vector lt int gt  used colors          vector lt int gt  used indices           auto getOne      vector lt int gt  amp  v  int c                int r              do                   r   rand     c                while  find v begin    v end    r     v end                 v push back r               return r                      for  auto i   0  i  lt  pairCount  i                  auto sock color   getOne used colors  INT MAX               socks getOne used indices  elemCount     sock color              socks getOne used indices  elemCount     sock color                       void show const string amp  prompt            cout  lt  lt  prompt  lt  lt   quot   quot   lt  lt  endl          for  auto i   0  i  lt  socks size    i                 cout  lt  lt  socks i   lt  lt   quot   quot                     cout  lt  lt  endl             void pair             for  auto i   0  i  lt  socks size    i                  std  vector lt int gt   iterator it   find unpaired socks begin    unpaired socks end    socks i                if  it    unpaired socks end                      unpaired socks erase it                   paired socks push back socks i                    paired socks push back socks i                              else                 unpaired socks push back socks i                       socks   paired socks          paired socks clear           private      int elemCount      vector lt int gt  socks      vector lt int gt  unpaired socks      vector lt int gt  paired socks      int main         pileOfsocks socks       socks show  quot unpaired socks quot        socks pair        socks show  quot paired socks quot         system  quot pause quot        return 0

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The problem of sorting your n pairs of socks is O n   Before you throw them in the laundry basket  you thread the left one to the right one  On taking them out  you cut the thread and put each pair into your drawer - 2 operations on n pairs  so O n    Now the next question is simply whether you do your own laundry and your wife does hers  That is a problem likely in an entirely different domain of problems

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You are trying to solve the wrong problem   Solution 1  Each time you put dirty socks in your laundry basket  tie them in a little knot  That way you will not have to do any sorting after the washing  Think of it like registering an index in a Mongo database  A little work ahead for some CPU savings in the future   Solution 2  If it s winter  you don t have to wear matching socks  We are programmers  Nobody needs to know  as long as it works   Solution 3  Spread the work  You want to perform such a complex CPU process asynchronously  without blocking the UI  Take that pile of socks and stuff them in a bag  Only look for a pair when you need it  That way the amount of work it takes is much less noticeable   Hope this helps

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Socks  whether real ones or some analogous data structure  would be supplied in pairs    The simplest answer is prior to allowing the pair to be separated  a single data structure for the pair should have been initialized that contained a pointer to the left and right sock  thus enabling socks to be referred to directly or via their pair  A sock may also be extended to contain a pointer to its partner   This solves any computational pairing problem by removing it with a layer of abstraction   Applying the same idea to the practical problem of pairing socks  the apparent answer is  don t allow your socks to ever be unpaired  Socks are provided as a pair  put in the drawer as a pair  perhaps by balling them together   worn as a pair  But the point where unpairing is possible is in the washer  so all that s required is a physical mechanism that allows the socks to stay together and be washed efficiently    There are two physical possibilities   For a  pair  object that keeps a pointer to each sock we could have a cloth bag that we use to keep the socks together  This seems like massive overhead   But for each sock to keep a reference to the other  there is a neat solution  a popper  or a  snap button  if you re American   such as these   http   www aliexpress com compare compare-invisible-snap-buttons html  Then all you do is snap your socks together right after you take them off and put them in your washing basket  and again you ve removed the problem of needing to pair your socks with a physical abstraction of the  pair  concept

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In order to say how efficient it is to pair socks from a pile  we have to define the machine first  because the pairing isn t done whether by a turing nor by a random access machine  which are normally used as the basis for an algorithmic analysis  The machine The machine is an abstraction of a the real world element called human being  It is able to read from the environment via a pair of eyes  And our machine model is able to manipulate the environment by using 2 arms  Logical and arithmetic operations are calculated using our brain  hopefully  -    We also have to consider the intrinsic runtime of the atomic operations that can be carried out with these instruments  Due to physical constraints  operations which are carried out by an arm or eye have non constant time complexity  This is because we can t move an endlessly large pile of socks with an arm nor can an eye see the top sock on an endlessly large pile of socks  However mechanical physics give us some goodies as well  We are not limited to move at most one sock with an arm  We can move a whole couple of them at once  So depending on the previous analysis following operations should be used in descending order   logical and arithmetic operations environmental reads environmental modifications  We can also make use of the fact that people only have a very limited amount of socks  So an environmental modification can involve all socks in the pile  The algorithm So here is my suggestion   Spread all socks in the pile over the floor  Find a pair by looking at the socks on the floor  Repeat from 2 until no pair can be made  Repeat from 1 until there are no socks on the floor   Operation 4 is necessary  because when spreading socks over the floor some socks may hide others  Here is the analysis of the algorithm  The analysis The algorithm terminates with high probability  This is due to the fact that one is unable to find pairs of socks in step number 2  For the following runtime analysis of pairing n pairs of socks  we suppose that at least half of the 2n socks aren t hidden after step 1  So in the average case we can find n 2 pairs  This means that the loop is step 4 is executed O log n  times  Step 2 is executed O n 2  times  So we can conclude   The algorithm involves O ln n   n  environmental modifications  step 1 O ln n  plus picking every pair of sock from the floor  The algorithm involves O n 2  environmental reads from step 2 The algorithm involves O n 2  logical and arithmetic operations for comparing a sock with another in step 2  So we have a total runtime complexity of O r n 2   w  ln n   n   where r and w are the factors for environmental read and environmental write operations respectively for a reasonable amount of socks  The cost of the logical and arithmetical operations are omitted  because we suppose that it takes a constant amount of logical and arithmetical operations to decide whether 2 socks belong to the same pair  This may not be feasible in every scenario

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Cost  Moving socks -  high  finding search socks in line -  small  What we want to do is reduce the number of moves  and compensate with the number of searches  Also  we can utilize the multithreded environment of the Homo Sapiens to hold more things in the descision cache    X   Yours  Y   Your spouses  From pile A of all socks   Pick two socks  place corresponding X sock in X line  and Y sock in Y line at next available position   Do until A is empty   For each line X and Y   Pick the first sock in line  search along the line until it finds the corresponding sock  Put into the corresponding finished line of socks   Optional While you are searching the line and and the current sock you are looking at is identical to the previous  do step 2 for these socks    Optionally to step one  you pick up two sock from that line instead of two  as the caching memory is large enough we can quickly identify if either sock matches the current one on the line you are observing  If you are fortunate enough to have three arms  you could possibly parse three socks at the same time given that the memory of the subject is large enough   Do until both X and Y is empty   Done  However  as this have simillar complexity as selection sort  the time taken is far less due to the speeds of I O moving socks  and search searching the line for a sock

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Pick up a first sock and place it on a table  Now pick another sock  if it matches the first picked  place it on top of the first  If not  place it on the table a small distance from the first  Pick a third sock  if it matches either of the previous two  place it on top of them or else place it a small distance from the third  Repeat until you have picked up all the socks

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My solution does not exactly correspond to your requirements  as it formally requires O n   extra  space  However  considering my conditions it is very efficient in my practical application  Thus I think it should be interesting   Combine with Other Task  The special condition in my case is that I don t use drying machine  just hang my cloths on an ordinary cloth dryer  Hanging cloths requires O n  operations  by the way  I always consider bin packing problem here  and the problem by its nature requires the linear  extra  space  When I take a new sock from the bucket I to try hang it next to its pair if the pair is already hung  If its a sock from a new pair I leave some space next to it    Oracle Machine is Better  -   It obviously requires some extra work to check if there is the matching sock already hanging somewhere and it would render solution O n 2  with coefficient about 1 2 for a computer  But in this case the  human factor  is actually an advantage -- I usually can very quickly  almost O 1   identify the matching sock if it was already hung  probably some imperceptible in-brain caching is involved  -- consider it a kind of limited  oracle  as in Oracle Machine  -  We  the humans have these advantages over digital machines in some cases  -   Have it Almost O n    Thus connecting the problem of pairing socks with the problem of hanging cloths I get O n   extra space  for free  and have a solution that is about O n  in time  requires just a little more work than simple hanging cloths and allows to immediately access complete pair of socks even in a very bad Monday morning     -

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This is how I actually do it  for p pairs of socks  n   2p individual socks     Grab a sock at random from the pile  For the first sock  or if all previously-chosen socks have been paired  simply place the sock into the first  slot  of an  array  of unpaired socks in front of you  If you have one or more selected unpaired socks  check your current sock against all the unpaired socks in the array    It is possible to separate socks into general classes or types  white black  ankle crew  athletic dress  when building your array  and  drill-down  to only compare like-for-like  If you find an acceptable match  put both socks together and remove them from the array  If you do not  put the current sock into the first open slot in the array   Repeat with every sock    The worst-case scenario of this scheme is that every pair of socks is different enough that it must be matched exactly  and that the first n 2 socks you pick are all different  This is your O n2  scenario  and it s extremely unlikely  If the number of unique types of sock t is less than the number of pairs p   n 2  and the socks in each type are alike enough  usually in wear-related terms  that any sock of that type can be paired with any other  then as I inferred above  the maximum number of socks you will ever have to compare to is t  after which the next one you pull will match one of the unpaired socks  This scenario is much more likely in the average sock drawer than the worst-case  and reduces the worst-case complexity to O n t  where usually t  lt  lt  n

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This question is actually deeply philosophical  At heart it s about whether the power of people to solve problems  the  wetware  of our brains  is equivalent to what can be accomplished by algorithms   An obvious algorithm for sock sorting is   Let N be the set of socks that are still unpaired  initially empty for each sock s taken from the dryer   if s matches a sock t in N     remove t from N  bundle s and t together  and throw them in the basket   else     add s to N   Now the computer science in this problem is all about the steps    if s pairs with a sock t in N    How quickly can we  remember  what we ve seen so far   remove t from N  and  add s to N    How expensive is keeping track of what we ve seen so far    Human beings will use various strategies to effect these  Human memory is associative  something like a hash table where feature sets of stored values are paired with the corresponding values themselves  For example  the concept of  red car  maps to all the red cars a person is capable of remembering  Someone with a perfect memory has a perfect mapping   Most people are imperfect in this regard  and most others    The associative map has a limited capacity  Mappings may bleep out of existence under various circumstances  one beer too many   be recorded in error   I though her name was Betty  not Nettie    or never be overwritten even though we observe that the truth has changed   dad s car  evokes  orange Firebird  when we actually knew he d traded that in for the red Camaro    In the case of socks  perfect recall means looking at a sock s always produces the memory of its sibling t  including enough information  where it is on the ironing board  to locate t in constant time   A person with photographic memory accomplishes both 1 and 2 in constant time without fail   Someone with less than perfect memory might use a few commonsense equivalence classes based on features within his capability to track  size  papa  mama  baby   color  greenish  redish  etc    pattern  argyle  plain  etc    style  footie  knee-high  etc     So the ironing board would be divided into sections for the categories  This usually allows the category to be located in constant time by memory  but then a linear search through the category  bucket  is needed    Someone with no memory or imagination at all  sorry  will just keep the socks in one pile and do a linear search of the whole pile   A neat freak might use numeric labels for pairs as someone suggested   This opens the door to a total ordering  which allows the human to use exactly the same algorithms we might with a CPU  binary search  trees  hashes  etc   So the  best  algorithm depends on the qualities of the wetware hardware software that is running it and our willingness to  cheat  by imposing a total order on pairs   Certainly a  best  meta-algorithm is to hire the worlds best sock-sorter  a person or machine that can aquire and quickly store a huge set N of sock attribute sets in a 1-1 associative memory with constant time lookup  insert  and delete  Both people and machines like this can be procured  If you have one  you can pair all the socks in O N  time for N pairs  which is optimal  The total order tags allow you to use standard hashing to get the same result with either a human or hardware computer

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Create a hash table which will be used for unmatched socks  using the pattern as the hash  Iterate over the socks one by one  If the sock has a pattern match in the hash table  take the sock out of the table and make a pair  If the sock does not have a match  put it into the table

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Two lines of thinking  the speed it takes to find any match  versus the speed it takes to find all matches compared to the storage   For the second case  I wanted to point out a GPU paralleled version which queries the socks for all matches   If you have multiple properties for which to match  you can make use of grouped tuples and fancier zip iterators and the transform functions of thrust  for simplicity sake though here is a simple GPU based query     test cu  include  lt thrust device vector h gt   include  lt thrust sequence h gt   include  lt thrust copy h gt   include  lt thrust count h gt   include  lt thrust remove h gt   include  lt thrust random h gt   include  lt iostream gt   include  lt iterator gt   include  lt string gt      Define some types for pseudo code readability typedef thrust  device vector lt int gt  GpuList  typedef GpuList  iterator          GpuListIterator   template  lt typename T gt  struct ColoredSockQuery   public thrust  unary function lt T bool gt        ColoredSockQuery  int colorToSearch         SockColor   colorToSearch         int SockColor         host     device       bool operator   T x                return x    SockColor             struct GenerateRandomSockColor       float lowBounds  highBounds         host     device       GenerateRandomSockColor int  a  0  int  b  1    lowBounds  a   highBounds  b             host     device       int operator   const unsigned int n  const               thrust  default random engine rng          thrust  uniform real distribution lt float gt  dist lowBounds  highBounds           rng discard n           return dist rng             template  lt typename GpuListIterator gt  void PrintSocks const std  string amp  name  GpuListIterator first  GpuListIterator last        typedef typename std  iterator traits lt GpuListIterator gt   value type T       std  cout  lt  lt  name  lt  lt            thrust  copy first  last  std  ostream iterator lt T gt  std  cout             std  cout  lt  lt    n      int main         int numberOfSocks   10000000      GpuList socks numberOfSocks       thrust  transform thrust  make counting iterator 0                         thrust  make counting iterator numberOfSocks                         socks begin                          GenerateRandomSockColor 0  200         clock t start   clock         GpuList sortedSocks socks size         GpuListIterator lastSortedSock   thrust  copy if socks begin                                                         socks end                                                         sortedSocks begin                                                         ColoredSockQuery lt int gt  2        clock t stop   clock         PrintSocks  Sorted Socks     sortedSocks begin    lastSortedSock        double elapsed    double  stop - start    1000 0   CLOCKS PER SEC      std  cout  lt  lt   Time elapsed in ms     lt  lt  elapsed  lt  lt    n        return 0           nvcc -std c  11 -o test test cu   Run time for 10 million socks  9 ms

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What I do is that I pick up the first sock and put it down  say  on the edge of the laundry bowl   Then I pick up another sock and check to see if it s the same as the first sock  If it is  I remove them both  If it s not  I put it down next to the first sock  Then I pick up the third sock and compare that to the first two  if they re still there   Etc   This approach can be fairly easily be implemented in an array  assuming that  removing  socks is an option  Actually  you don t even need to  remove  socks  If you don t need sorting of the socks  see below   then you can just move them around and end up with an array that has all the socks arranged in pairs in the array   Assuming that the only operation for socks is to compare for equality  this algorithm is basically still an n2 algorithm  though I don t know about the average case  never learned to calculate that    Sorting  of course improves efficiency  especially in real life where you can easily  insert  a sock between two other socks  In computing the same could be achieved by a tree  but that s extra space  And  of course  we re back at NlogN  or a bit more  if there are several socks that are the same by sorting criteria  but not from the same pair    Other than that  I cannot think of anything  but this method does seem to be pretty efficient in real life

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I came out with another solution which would not promise fewer operations  neither less time consumption  but it should be tried to see if it can be a good-enough heuristic to provide less time consumption in huge series of sock pairing   Preconditions  There is no guarantee that there are the same socks  If they are of the same color it doesn t mean they have the same size or pattern  Socks are randomly shuffled  There can be odd number of socks  some are missing  we don t know how many   Prepare to remember a variable  index  and set it to 0   The result will have one or two piles  1   matched  and 2   missing   Heuristic    Find most distinctive sock  Find its match  If there is no match  put it on the  missing  pile  Repeat from 1  until there are no more most distinctive socks  If there are less then 6 socks  go to 11  Pair blindly all socks to its neighbor  do not pack it  Find all matched pairs  pack it and move packed pairs to  matched  pile   If there were no new matches - increment  index  by 1 If  index  is greater then 2  this could be value dependent on sock  number because with greater number of socks there are less chance to   pair them blindly  go to 11 Shuffle the rest Go to 1 Forget  index  Pick a sock Find its pair If there is no pair for the sock  move it to the  missing  pile If match found pair it  pack pair and move it to the  matched  pile If there are still more then one socks go to 12 If there is just one left go to 14 Smile satisfied      Also  there could be added check for damaged socks also  as if the removal of those  It could be inserted between 2 and 3  and between 13 and 14   I m looking forward to hear about any experiences or corrections

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As the architecture of the human brain is completely different than a modern CPU  this question makes no practical sense   Humans can win over CPU algorithms using the fact that  finding a matching pair  can be one operation for a set that isn t too big   My algorithm   spread all socks on flat surface    while  socks left on a surface              Thanks to human visual SIMD  this is one  quick operation       pair   notice any matching pair         remove socks pair from surface pair       At least this is what I am using in real life  and I find it very efficient  The downside is it requires a flat surface  but it s usually abundant

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Whenever you pick up a sock  put it in one place   Then the next sock you pick up  if it doesn t match the first sock  set it beside the first one   If it does  there s a pair   This way it doesn t really matter how many combinations there are  and there are only two possibilities for each sock you pick up -- either it has a match that s already in your array of socks  or it doesn t  which means you add it to a place in the array   This also means that you will almost certainly never have all your socks in the array  because socks will get removed as they re matched

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Non-algorithmic answer  yet  efficient  when I do it    step 1  discard all your existing socks step 2  go to Walmart and buy them by packets of 10 - n packet of white and m packets of black  No need for other colors in everyday s life    Yet times to times  I have to do this again  lost socks  damaged socks  etc    and I hate to discard perfectly good socks too often  and I wished they kept selling the same socks reference    so I recently took a different approach   Algorithmic answer   Consider than if you draw only one sock for the second stack of socks  as you are doing  your odds of finding the matching sock in a naive search is quite low    So pick up five of them at random  and memorize their shape or their length    Why five  Usually humans are good are remembering between five and seven different elements in the working memory - a bit like the human equivalent of a RPN stack - five is a safe default    Pick up one from the stack of 2n-5  Now look for a match  visual pattern matching - humans are good at that with a small stack  inside the five you drew  if you don t find one  then add that to your five  Keep randomly picking socks from the stack and compare to your 5 1 socks for a match  As your stack grows  it will reduce your performance but raise your odds  Much faster    Feel free to write down the formula to calculate how many samples you have to draw for a 50  odds of a match  IIRC it s an hypergeometric law   I do that every morning and rarely need more than three draws - but I have n similar pairs  around 10  give or take the lost ones  of m shaped white socks  Now you can estimate the size of my stack of stocks  -   BTW  I found that the sum of the transaction costs of sorting all the socks every time I needed a pair were far less than doing it once and binding the socks  A just-in-time works better because then you don t have to bind the socks  and there s also a diminishing marginal return  that is  you keep looking for that two or three socks that when somewhere in the laundry and that you need to finish matching your socks and you lose time on that

[algorithm] How can I pair socks from a pile efficiently?

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