genetic algorithm - Page 62

Ranking/ weighing search result

- by biso

I am trying to build an application that has a smart adaptive search engine (lets say for cars). If I search for for 4x4 then the DB will return all the 4x4 cars I have (100 cars) - but as time goes by and I start checking out cars, liking them, commenting on them, etc the order of the search result should be the different. That means 1 month later when searching for 4x4, I should get the same result set ordered differently as per my previous interaction with the site. If I was mainly liking and commenting on German cars, BMW should be on the top and Land cruiser should be further down. This ranking should be based on attributes that I captureduring user interaction (eg: car origin, user age, user location, car type[4x4, coupe, hatchback], price range). So for each car result I get, I will be weighing it based on how well it is performing on the 5 attributes above. I intend to use the DB just as a repository and do the ranking and the thinking on the server. My question is, what kind of algorithm should I be using to weigh/rank my search result? Thanks.

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Fastest way to convert a list of doubles to a unique list of integers?

- by javanix

I am dealing with a MySQL table here that is keyed in a somewhat unfortunate way. Instead of using an auto increment table as a key, it uses a column of decimals to preserve order (presumably so its not too difficult to insert new rows while preserving a primary key and order). Before I go through and redo this table to something more sane, I need to figure out how to rekey it without breaking everything. What I would like to do is something that takes a list of doubles (the current keys) and outputs a list of integers (which can be cast down to doubles for rekeying). For example, input {1.00, 2.00, 2.50, 2.60, 3.00} would give output {1, 2, 3, 4, 5). Since this is a database, I also need to be able to update the rows nicely: UPDATE table SET `key`='3.00' WHERE `key`='2.50'; Can anyone think of a speedy algorithm to do this? My current thought is to read all of the doubles into a vector, take the size of the vector, and output a new vector with values from 1 => doubleVector.size. This seems pretty slow, since you wouldn't want to read every value into the vector if, for instance, only the last n/100 elements needed to be modified. I think there is probably something I can do in place, since only values after the first non-integer double need to be modified, but I can't for the life of me figure anything out that would let me update in place as well. For instance, setting 2.60 to 3.00 the first time you see 2.50 in the original key list would result in an error, since the key value 3.00 is already used for the table.

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Find min. "join" operations for sequence

- by utyle

Let's say, we have a list/an array of positive integers x1, x2, ... , xn. We can do a join operation on this sequence, that means that we can replace two elements that are next to each other with one element, which is sum of these elements. For example: - array/list: [1;2;3;4;5;6] we can join 2 and 3, and replace them with 5; we can join 5 and 6, and replace them with 11; we cannot join 2 and 4; we cannot join 1 and 3 etc. Main problem is to find minimum join operations for given sequence, after which this sequence will be sorted in increasing order. Note: empty and one-element sequences are sorted in increasing order. Basic examples: for [4; 6; 5; 3; 9] solution is 1 (we join 5 and 3) for [1; 3; 6; 5] solution is also 1 (we join 6 and 5) What I am looking for, is an algorithm that solve this problem. It could be in pseudocode, C, C++, PHP, OCaml or similar (I mean: I woluld understand solution, if You wrote solution in one of these languages). I would appreciate Your help.

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how to implement a really efficient bitvector sorting in python

- by xiao

Hello guys! Actually this is an interesting topic from programming pearls, sorting 10 digits telephone numbers in a limited memory with an efficient algorithm. You can find the whole story here What I am interested in is just how fast the implementation could be in python. I have done a naive implementation with the module bitvector. The code is as following: from BitVector import BitVector import timeit import random import time import sys def sort(input_li): return sorted(input_li) def vec_sort(input_li): bv = BitVector( size = len(input_li) ) for i in input_li: bv[i] = 1 res_li = [] for i in range(len(bv)): if bv[i]: res_li.append(i) return res_li if __name__ == "__main__": test_data = range(int(sys.argv[1])) print 'test_data size is:', sys.argv[1] random.shuffle(test_data) start = time.time() sort(test_data) elapsed = (time.time() - start) print "sort function takes " + str(elapsed) start = time.time() vec_sort(test_data) elapsed = (time.time() - start) print "sort function takes " + str(elapsed) start = time.time() vec_sort(test_data) elapsed = (time.time() - start) print "vec_sort function takes " + str(elapsed) I have tested from array size 100 to 10,000,000 in my macbook(2GHz Intel Core 2 Duo 2GB SDRAM), the result is as following: test_data size is: 1000 sort function takes 0.000274896621704 vec_sort function takes 0.00383687019348 test_data size is: 10000 sort function takes 0.00380706787109 vec_sort function takes 0.0371489524841 test_data size is: 100000 sort function takes 0.0520560741425 vec_sort function takes 0.374383926392 test_data size is: 1000000 sort function takes 0.867373943329 vec_sort function takes 3.80475401878 test_data size is: 10000000 sort function takes 12.9204008579 vec_sort function takes 38.8053860664 What disappoints me is that even when the test_data size is 100,000,000, the sort function is still faster than vec_sort. Is there any way to accelerate the vec_sort function?

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Does anyone knows the algorithm how Facebook detects the images when adding a link

- by Edelcom

When you add a link to your Facebook page, after some processing, Facebook presents you a next/prev button to choose an image linked to the url your are inserting. Obviously, Facebook reads the html-page and displays the images found on the url you insert. Does anyone knows what algorithm Facebook uses to decide what images to show ? If I insert a link to : http://www.staplijst.be/lachende-wandelaars-aalter-aktivia-003.asp, only 11 images are detected. The one I want, the one at the top right corner, is not included in the list. If I insert a link to http://www.staplijst.be/stichting-kennedymars-rijsbergen-zundert-nederland-knblo-nl-81996.asp, 19 images are displayed (including the one I want (the one at the right top corner of the text area). Both pages are build using asp code but are functionally the same. I thought that it has something to do with the image size, but can't find any deciding factor there. I will investigate some furhter, because if I know what Facebook is looking for, I can make sure that the correct images are included on the page (since they are dynamic pages build with classic asp). But if anyone has any idea ? Help would be appreciated.

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Good PHP / MYSQL hashing solution for large number of text values

- by Dave

Short descriptio: Need hashing algorithm solution in php for large number of text values. Long description. PRODUCT_OWNER_TABLE serial_number (auto_inc), product_name, owner_id OWNER_TABLE owner_id (auto_inc), owener_name I need to maintain a database of 200000 unique products and their owners (AND all subsequent changes to ownership). Each product has one owner, but an owner may have MANY different products. Owner names are "Adam Smith", "John Reeves", etc, just text values (quite likely to be unicode as well). I want to optimize the database design, so what i was thinking was, every week when i run this script, it fetchs the owner of a proudct, then checks against a table i suppose similar to PRODUCT_OWNER_TABLE, fetching the owner_id. It then looks up owner_id in OWNER_TABLE. If it matches, then its the same, so it moves on. The problem is when its different... To optimize the database, i think i should be checking against the other "owner_name" entries in OWNER_TABLE to see if that value exists there. If it does, then i should use that owner_id. If it doesnt, then i should add another entry. Note that there is nothing special about the "name". as long as i maintain the correct linkagaes AND make the OWNER_TABLE "read-only, append-new" type table - I should be able create a historical archive of ownership. I need to do this check for 200000 entries, with i dont know how many unique owner names (~50000?). I think i need a hashing solution - the OWNER_TABLE wont be sorted, so search algos wont be optimal. programming language is PHP. database is MYSQL.

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Ideas Related to Subset Sum with 2,3 and more integers

- by rolandbishop

I've been struggling with this problem just like everyone else and I'm quite sure there has been more than enough posts to explain this problem. However in terms of understanding it fully, I wanted to share my thoughts and get more efficient solutions from all the great people in here related to Subset Sum problem. I've searched it over the Internet and there is actually a lot sources but I'm really willing to re-implement an algorithm or finding my own in order to understand fully. The key thing I'm struggling with is the efficiency considering the set size will be large. (I do not have a limit, just conceptually large). The two phases I'm trying to implement ideas on is finding two numbers that are equal to given integer T, finding three numbers and eventually K numbers. Some ideas I've though; For the two integer part I'm thing basically sorting the array O(nlogn) and for each element in the array searching for its negative value. (i.e if the array element is 3 searching for -3). Maybe a hash table inclusion could be better, providing a O(1) indexing the element? For the three or more integers I've found an amazing blog post;http://www.skorks.com/2011/02/algorithms-a-dropbox-challenge-and-dynamic-programming/. However even the author itself states that it is not applicable for large numbers. So I was for 2 and 3 and more integers what ideas could be applied for the subset problem. I'm struggling with setting up a dynamic programming method that will be efficient for the large inputs as well.

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Reversing permutation of an array in Java efficiently

- by HansDampf

Okay, here is my problem: Im implementing an algorithm in Java and part of it will be following: The Question is to how to do what I will explain now in an efficient way. given: array a of length n integer array perm, which is a permutation of [1..n] now I want to shuffle the array a, using the order determined by array perm, i.e. a=[a,b,c,d], perm=[2,3,4,1] ------ shuffledA[b,c,d,a], I figured out I can do that by iterating over the array with: shuffledA[i]=a[perm[i-1]], (-1 because the permutation indexes in perm start with 1 not 0) Now I want to do some operations on shuffledA... And now I want to do the reverse the shuffle operation. This is where I am not sure how to do it. Note that a can hold an item more than once, i.e. a=[a,a,a,a] If that was not the case, I could iterate perm, and find the corresponding indexes to the values. Now I thought that using a Hashmap instead of the the perm array will help. But I am not sure if this is the best way to do.

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Designing small comparable objects

- by Thomas Ahle

Intro Consider you have a list of key/value pairs: (0,a) (1,b) (2,c) You have a function, that inserts a new value between two current pairs, and you need to give it a key that keeps the order: (0,a) (0.5,z) (1,b) (2,c) Here the new key was chosen as the average between the average of keys of the bounding pairs. The problem is, that you list may have milions of inserts. If these inserts are all put close to each other, you may end up with keys such to 2^(-1000000), which are not easily storagable in any standard nor special number class. The problem How can you design a system for generating keys that: Gives the correct result (larger/smaller than) when compared to all the rest of the keys. Takes up only O(logn) memory (where n is the number of items in the list). My tries First I tried different number classes. Like fractions and even polynomium, but I could always find examples where the key size would grow linear with the number of inserts. Then I thought about saving pointers to a number of other keys, and saving the lower/greater than relationship, but that would always require at least O(sqrt) memory and time for comparison. Extra info: Ideally the algorithm shouldn't break when pairs are deleted from the list.

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Find all ways to insert zeroes into a bit pattern

- by James

I've been struggling to wrap my head around this for some reason. I have 15 bits that represent a number. The bits must match a pattern. The pattern is defined in the way the bits start out: they are in the most flush-right representation of that pattern. So say the pattern is 1 4 1. The bits will be: 000000010111101 So the general rule is, take each number in the pattern, create that many bits (1, 4 or 1 in this case) and then have at least one space separating them. So if it's 1 2 6 1 (it will be random): 001011011111101 Starting with the flush-right version, I want to generate every single possible number that meets that pattern. The # of bits will be stored in a variable. So for a simple case, assume it's 5 bits and the initial bit pattern is: 00101. I want to generate: 00101 01001 01010 10001 10010 10100 I'm trying to do this in Objective-C, but anything resembling C would be fine. I just can't seem to come up with a good recursive algorithm for this. It makes sense in the above example, but when I start getting into 12431 and having to keep track of everything it breaks down.

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Ad distribution problem: an optimal solution?

- by Mokuchan

I'm asked to find a 2 approximate solution to this problem: You’re consulting for an e-commerce site that receives a large number of visitors each day. For each visitor i, where i € {1, 2 ..... n}, the site has assigned a value v[i], representing the expected revenue that can be obtained from this customer. Each visitor i is shown one of m possible ads A1, A2 ..... An as they enter the site. The site wants a selection of one ad for each customer so that each ad is seen, overall, by a set of customers of reasonably large total weight. Thus, given a selection of one ad for each customer, we will define the spread of this selection to be the minimum, over j = 1, 2 ..... m, of the total weight of all customers who were shown ad Aj. Example Suppose there are six customers with values 3, 4, 12, 2, 4, 6, and there are m = 3 ads. Then, in this instance, one could achieve a spread of 9 by showing ad A1 to customers 1, 2, 4, ad A2 to customer 3, and ad A3 to customers 5 and 6. The ultimate goal is to find a selection of an ad for each customer that maximizes the spread. Unfortunately, this optimization problem is NP-hard (you don’t have to prove this). So instead give a polynomial-time algorithm that approximates the maximum spread within a factor of 2. The solution I found is the following: Order visitors values in descending order Add the next visitor value (i.e. assign the visitor) to the Ad with the current lowest total value Repeat This solution actually seems to always find the optimal solution, or I simply can't find a counterexample. Can you find it? Is this a non-polinomial solution and I just can't see it?

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How do I create a graph from this datastructure?

- by Shawn Mclean

I took this data structure from this A* tutorial: public interface IHasNeighbours<N> { IEnumerable<N> Neighbours { get; } } public class Path<TNode> : IEnumerable<TNode> { public TNode LastStep { get; private set; } public Path<TNode> PreviousSteps { get; private set; } public double TotalCost { get; private set; } private Path(TNode lastStep, Path<TNode> previousSteps, double totalCost) { LastStep = lastStep; PreviousSteps = previousSteps; TotalCost = totalCost; } public Path(TNode start) : this(start, null, 0) { } public Path<TNode> AddStep(TNode step, double stepCost) { return new Path<TNode>(step, this, TotalCost + stepCost); } public IEnumerator<TNode> GetEnumerator() { for (Path<TNode> p = this; p != null; p = p.PreviousSteps) yield return p.LastStep; } IEnumerator IEnumerable.GetEnumerator() { return this.GetEnumerator(); } } I have no idea how to create a simple graph with. How do I add something like the following undirected graph using C#: Basically I'd like to know how to connect nodes. I have my own datastructures that I can already determine the neighbors and the distance. I'd now like to convert that into this posted datastructure so I can run it through the AStar algorithm. I was seeking something more like: Path<EdgeNode> startGraphNode = new Path<EdgeNode>(tempStartNode); startGraphNode.AddNeighbor(someOtherNode, distance);

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minimum L sum in a mxn matrix - 2

- by hilal

Here is my first question about maximum L sum and here is different and hard version of it. Problem : Given a mxn *positive* integer matrix find the minimum L sum from 0th row to the m'th row . L(4 item) likes chess horse move Example : M = 3x3 0 1 2 1 3 2 4 2 1 Possible L moves are : (0 1 2 2), (0 1 3 2) (0 1 4 2) We should go from 0th row to the 3th row with minimum sum I solved this with dynamic-programming and here is my algorithm : 1. Take a mxn another Minimum L Moves Sum array and copy the first row of main matrix. I call it (MLMS) 2. start from first cell and look the up L moves and calculate it 3. insert it in MLMS if it is less than exists value 4. Do step 2. until m'th row 5. Choose the minimum sum in the m'th row Let me explain on my example step by step: M[ 0 ][ 0 ] sum(L1 = (0, 1, 2, 2)) = 5 ; sum(L2 = (0,1,3,2)) = 6; so MLMS[ 0 ][ 1 ] = 6 sum(L3 = (0, 1, 3, 2)) = 6 ; sum(L4 = (0,1,4,2)) = 7; so MLMS[ 2 ][ 1 ] = 6 M[ 0 ][ 1 ] sum(L5 = (1, 0, 1, 4)) = 6; sum(L6 = (1,3,2,4)) = 10; so MLMS[ 2 ][ 2 ] = 6 ... the last MSLS is : 0 1 2 4 3 6 6 6 6 Which means 6 is the minimum L sum that can be reach from 0 to the m. I think it is O(8*(m-1)*n) = O(m*n). Is there any optimal solution or dynamic-programming algorithms fit this problem? Thanks, sorry for long question

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What is the complexity of this specialized sort

- by ADB

I would like to know the complexity (as in O(...) ) of the following sorting algorithm: there are B barrels that contains a total of N elements, spread unevenly across the barrels. the elements in each barrel are already sorted The sort takes combines all the elements from each barrel in a single sorted list: using an array of size B to store the last sorted element of each barrel (starting at 0) check each barrel (at the last stored index) and find the smallest element copy the element in the final sorted array, increment array counter increment the last sorted element for the barrel we picked from perform those steps N times or in pseudo: for i from 0 to N smallest = MAX_ELEMENT foreach b in B if bIndex[b] < b.length && b[bIndex[b]] < smallest smallest_barrel = b smallest = b[bIndex[b]] result[i] = smallest bIndex[smallest_barrel] += 1 I thought that the complexity would be O(n), but the problem I have with finding the complexity is that if B grows, it has a larger impact than if N grows because it adds another round in the B loop. But maybe that has no effect on the complexity?

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How to convert between different currencies?

- by sil3nt

Hey there, this is part of a question i got in class, im at the final stretch but this has become a major problem. In it im given a certain value which is called the "gold value" and it is 40.5, this value changes in input. and i have these constants const int RUBIES_PER_DIAMOND = 5; // relative values. * const int EMERALDS_PER_RUBY = 2; const int GOLDS_PER_EMERALDS = 5; const int SILVERS_PER_GOLD = 4; const int COPPERS_PER_SILVER = 5; const int DIAMOND_VALUE = 50; // gold values. * const int RUBY_VALUE = 10; const int EMERALD_VALUE = 5; const float SILVER_VALUE = 0.25; const float COPPER_VALUE = 0.05; which means that basically for every diamond there are 5 rubies, and for every ruby there are 2 emeralds. So on and so forth. and the "gold value" for every diamond for example is 50 (diamond value = 50) this is how much one diamond is worth in golds. my problem is converting 40.5 into these diamonds and ruby values. I know the answer is 4rubies and 2silvers but how do i write the algorithm for this so that it gives the best estimate for every goldvalue that comes along?? please help!, im at my wits end

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question about counting sort

- by davit-datuashvili

hi i have write following code which prints elements in sorted order only one big problem is that it use two additional array here is my code public class occurance{ public static final int n=5; public static void main(String[]args){ // n is maximum possible value what it should be in array suppose n=5 then array may be int a[]=new int[]{3,4,4,2,1,3,5};// as u see all elements are less or equal to n //create array a.length*n int b[]=new int[a.length*n]; int c[]=new int[b.length]; for (int i=0;i<b.length;i++){ b[i]=0; c[i]=0; } for (int i=0;i<a.length;i++){ if (b[a[i]]==1){ c[a[i]]=1; } else{ b[a[i]]=1; } } for (int i=0;i<b.length;i++){ if (b[i]==1) { System.out.println(i); } if (c[i]==1){ System.out.println(i); } } } } // 1 2 3 3 4 4 5 1.i have two question what is complexity of this algorithm?i mean running time 2. how put this elements into other array with sorted order? thanks

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How can I evaluate the connectedness of my nodes?

- by Travis Leleu

I've got a space that has nodes that are all interconnected, based on a "similarity score". I would like to determine how "connected" a node is with the others. My purpose is to find nodes that are poorly connected to make sure that the backlink from the other node is prioritized. Perhaps an example would help. I've got a web page that links to my other pages based on a similarity score. Suppose I have the pages: A, B, C, ... A has a backlink from every other page, so it's very well connected. It also has links to all my other pages (each line in the graph is essentially bidirectional). B only has 1 backlink, from A. C has a link from A and D. I would like to make sure that the A-B link is prioritized over the A-C link (even if the similarity score between C and A is higher than B and A). In short, I would like to evaluate which nodes are least and best connected, so that I can mangle the results to my means. I believe this is Graph Connectedness, but I'm at a loss to develop a (simple) algorithm that will help me here. Simply counting the backlinks to a node may be a starting point -- but then how do I take the next step, which is to properly weight the links on the original node (A, in the example above)?

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finding common prefix of array of strings

- by bumperbox

I have an array like this $sports = array( 'Softball - Counties', 'Softball - Eastern', 'Softball - North Harbour', 'Softball - South', 'Softball - Western' ); and i would like to find the longest common part of the string so in this instance, it would be 'Softball - '; I am thinking that I would follow the this process $i = 1; // loop to the length of the first string while ($i < strlen($sports[0]) { // grab the left most part up to i in length $match = substr($sports[0], 0, $i); // loop through all the values in array, and compare if they match foreach ($sports as $sport) { if ($match != substr($sport, 0, $i) { // didn't match, return the part that did match return substr($sport, 0, $i-1); } } // foreach // increase string length $i++; } // while // if you got to here, then all of them must be identical Questions is there a built in function or much simpler way of doing this ? for my 5 line array that is probably fine, but if i were to do several thousand line arrays, there would be a lot of overhead, so i would have to be move calculated with my starting values of $i, eg $i = halfway of string, if it fails, then $i/2 until it works, then increment $i by 1 until we succeed. so that we are doing the least number of comparisons to get a result If there a formula/algorithm out already out there for this kind of problem ? thanks alex

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What algorithms compute directions from point A to point B on a map?

- by A. Rex

How do map providers (such as Google or Yahoo! Maps) suggest directions? I mean, they probably have real-world data in some form, certainly including distances but also perhaps things like driving speeds, presence of sidewalks, train schedules, etc. But suppose the data were in a simpler format, say a very large directed graph with edge weights reflecting distances. I want to be able to quickly compute directions from one arbitrary point to another. Sometimes these points will be close together (within one city) while sometimes they will be far apart (cross-country). Graph algorithms like Dijkstra's algorithm will not work because the graph is enormous. Luckily, heuristic algorithms like A* will probably work. However, our data is very structured, and perhaps some kind of tiered approach might work? (For example, store precomputed directions between certain "key" points far apart, as well as some local directions. Then directions for two far-away points will involve local directions to a key points, global directions to another key point, and then local directions again.) What algorithms are actually used in practice? PS. This question was motivated by finding quirks in online mapping directions. Contrary to the triangle inequality, sometimes Google Maps thinks that X-Z takes longer and is farther than using an intermediate point as in X-Y-Z. But maybe their walking directions optimize for another parameter, too? PPS. Here's another violation of the triangle inequality that suggests (to me) that they use some kind of tiered approach: X-Z versus X-Y-Z. The former seems to use prominent Boulevard de Sebastopol even though it's slightly out of the way. (Edit: this example doesn't work anymore, but did at the time of the original post. The one above still works as of early November 2009.)

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Need Help finding an appropriate task assignment algorithm for a college project involving coordinat

- by Trif Mircea

I am a long time lurker here and have found over time many answers regarding jquery and web development topics so I decided to ask a question of my own. This time I have to create a c++ project for college which should help manage the workflow of a company providing all kinds of services through in the field teams. The ideas I have so far are: client-server application; the server is a dispatcher where all the orders from clients get and the clients are mobile devices (PDAs) each team in the field having one a order from a client is a task. Each task is made up of a series of subtasks. You have a database with estimations on how long a task should take to complete you also know what tasks or subtasks each team on the field can perform based on what kind of specialists made up the team (not going to complicate the problem by adding needed materials, it is considered that if a member of a team can perform a subtask he has the stuff needed) Now knowing these factors, what would a good task assignment algorithm be? The criteria is: how many tasks can a team do, how many tasks they have in the queue, it could also be location, how far away are they from the place but I don't think I can implement that.. It needs to be efficient and also to adapt quickly is the human dispatcher manually assigns a task. Any help or leads would be really appreciated. Also I'm not 100% sure in the idea so if you have another way you would go about creating such an application please share, even if it just a quick outline. I have to write a theoretical part too so even if the ideas are far more complex that what i outlined that would be ok ; I'd write those and implement what I can. Edit: C++ is the only language I know unfortunately.

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Optimally place a pie slice in a rectangle.

- by Lisa

Given a rectangle (w, h) and a pie slice with start angle and end angle, how can I place the slice optimally in the rectangle so that it fills the room best (from an optical point of view, not mathematically speaking)? I'm currently placing the pie slice's center in the center of the rectangle and use the half of the smaller of both rectangle sides as the radius. This leaves plenty of room for certain configurations. Examples to make clear what I'm after, based on the precondition that the slice is drawn like a unit circle: A start angle of 0 and an end angle of PI would lead to a filled lower half of the rectangle and an empty upper half. A good solution here would be to move the center up by 1/4*h. A start angle of 0 and an end angle of PI/2 would lead to a filled bottom right quarter of the rectangle. A good solution here would be to move the center point to the top left of the rectangle and to set the radius to the smaller of both rectangle sides. This is fairly easy for the cases I've sketched but it becomes complicated when the start and end angles are arbitrary. I am searching for an algorithm which determines center of the slice and radius in a way that fills the rectangle best. Pseudo code would be great since I'm not a big mathematician.

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Recursive code Sorting in VB

- by Peter

Ages old question: You have 2 hypothetical eggs, and a 100 story building to drop them from. The goal is to have the least number of guaranteed drops that will ensure you can find what floor the eggs break from the fall. You can only break 2 eggs. Using a 14 drop minimum method, I need help writing code that will allow me to calculate the following: Start with first drop attempt on 14th floor. If egg breaks then drop floors 1-13 to find the floor that causes break. ElseIf egg does not break then move up 13 floors to floor number 27 and drop again. If egg breaks then drop floors 15-26 starting on 15 working up to find the floor egg breaks on. ElseIf egg does not break then move up 12 floors to floor number 39 and drop again. etc. etc. The way this increases is as follows 14+13+12+11+10+9+8+7+6+5+4+3+2+1 So always adding to the previous value, by one less. I have never written a sorting algorithm before, and was curious how I might go about setting this up in a much more efficient way than a mile long of if then statements. My original idea was to store values for the floors in an array, and pull from that, using the index to move up or down and subtract or add to the variables. The most elegant solution would be a recursive function that handled this for any selected floor, 1-100, and ran the math, with an output that shows how many drops were needed in order to find that floor. Maximum is always 14, but some can be done in less.

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sum of square of each elements in the vector using for_each

- by pierr

Hi, As the function accepted by for_each take only one parameter (the element of the vector), I have to define a static int sum = 0 somewhere so that It can be accessed after calling the for_each . I think this is awkward. Any better way to do this (still use for_each) ? #include <algorithm> #include <vector> #include <iostream> using namespace std; static int sum = 0; void add_f(int i ) { sum += i * i; } void test_using_for_each() { int arr[] = {1,2,3,4}; vector<int> a (arr ,arr + sizeof(arr)/sizeof(arr[0])); for_each( a.begin(),a.end(), add_f); cout << "sum of the square of the element is " << sum << endl; } In Ruby, We can do it this way: sum = 0 [1,2,3,4].each { |i| sum += i*i} #local variable can be used in the callback function puts sum #=> 30 Would you please show more examples how for_each is typically used in practical programming (not just print out each element)? Is it possible use for_each simulate 'programming pattern' like map and inject in Ruby (or map /fold in Haskell). #map in ruby >> [1,2,3,4].map {|i| i*i} => [1, 4, 9, 16] #inject in ruby [1, 4, 9, 16].inject(0) {|aac ,i| aac +=i} #=> 30 EDIT: Thank you all. I have learned so much from your replies. We have so many ways to do the same single thing in C++ , which makes it a little bit difficult to learn. But it's interesting :)

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How to store visited states in iterative deepening / depth limited search?

- by colinfang

Update: Search for the first solution. for a normal Depth First Search it is simple, just use a hashset bool DFS (currentState) = { if (myHashSet.Contains(currentState)) { return; } else { myHashSet.Add(currentState); } if (IsSolution(currentState) return true; else { for (var nextState in GetNextStates(currentState)) if (DFS(nextState)) return true; } return false; } However, when it becomes depth limited, i cannot simply do this bool DFS (currentState, maxDepth) = { if (maxDepth = 0) return false; if (myHashSet.Contains(currentState)) { return; } else { myHashSet.Add(currentState); } if (IsSolution(currentState) return true; else { for (var nextState in GetNextStates(currentState)) if (DFS(nextState, maxDepth - 1)) return true; } return false; } Because then it is not going to do a complete search (in a sense of always be able to find a solution if there is any) before maxdepth How should I fix it? Would it add more space complexity to the algorithm? Or it just doesn't require to memoize the state at all. Update: for example, a decision tree is the following: A - B - C - D - E - A | F - G (Goal) Starting from state A. and G is a goal state. Clearly there is a solution under depth 3. However, using my implementation under depth 4, if the direction of search happens to be A(0) -> B(1) -> C(2) -> D(3) -> E(4) -> F(5) exceeds depth, then it would do back track to A, however E is visited, it would ignore the check direction A - E - F - G

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