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• How to implement a genetic algorithm with distance, time, and cost

  - by ari

  I want to make a solution to find the optimum route of school visit. For example, I want to visit 5 schools (A, B, C, D, E) in my city. Then I must find out what school I should visit first, then the second, then the third etc. with distance, time, and cost criteria. The problem is, I am confused about how to use distance with time and cost (fuel usage) estimation in genetic algorithm to find the optimum route?

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• Is the way I'm implementing my genetic algorithm right?

  - by Mhjr

  In my graduation project, I am asked to use a genetic algorithm (any variation of it can be chosen) to generate valid timetables. What I did was make a simple program that generates unique sequences representing genes, the sequence is described below: (sorry if it's mathematically incorrect) The only variable in the sequence is the room element, so basically the program takes a tree that goes like this: [Course] -(contains)-> [Units] -(contains)-> [Offerings] -(contains)-> [Instructors] -(contains)-> [Rooms] Each course can have n units (duplicates). Each unit can have n offerings (lectures,lab session, excercises,...). Each offering has only 1 instructor. Each instructor (or the whole lecture composed from the four elements of the sequence) has multiple rooms. When a timetable is initialized, one of these sequences that differ in rooms will be taken into the timetable, so the difference in genes (sequences) of each timetable will be just the rooms random choice and the difference between chromosomes (timetables) will be time placements of these genes (sequences). My question is, before I proceed in implementing what I described, is it valid? Is the representation used here for chromosomes a permutation representation?

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• A new mission statement for my school's algorithms class

  - by Eric Fode

  The teacher at Eastern Washington University that is now teaching the algorithms course is new to eastern and as a result the course has changed drastically mostly in the right direction. That being said I feel that the class could use a more specific, and industry oriented (since that is where most students will go, though suggestions for an academia oriented class are also welcome) direction, having only worked in industry for 2 years I would like the community's (a wider and much more collectively experienced and in the end plausibly more credible) opinion on the quality of this as a statement for the purpose an algorithms class, and if I am completely off target your suggestion for the purpose of a required Jr. level Algorithms class that is standalone (so no other classes focusing specifically on algorithms are required). The statement is as follows: The purpose of the algorithms class is to do three things: Primarily, to teach how to learn, do basic analysis, and implement a given algorithm found outside of the class. Secondly, to teach the student how to model a problem in their mind so that they can find a an existing algorithm or have a direction to start the development of a new algorithm. Third, to overview a variety of algorithms that exist and to deeply understand and analyze one algorithm in each of the basic algorithmic design strategies: Divide and Conquer, Reduce and Conquer, Transform and Conquer, Greedy, Brute Force, Iterative Improvement and Dynamic Programming. The Question in short is: do you agree with this statement of the purpose of an algorithms course, so that it would be useful in the real world, if not what would you suggest?

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• Genetic programming in c++, library suggestions?

  - by shuttle87

  I'm looking to add some genetic algorithms to an Operations research project I have been involved in. Currently we have a program that aids in optimizing some scheduling and we want to add in some heuristics in the form of genetic algorithms. Are there any good libraries for generic genetic programming/algorithms in c++? Or would you recommend I just code my own? I should add that while I am not new to c++ I am fairly new to doing this sort of mathematical optimization work in c++ as the group I worked with previously had tended to use a proprietary optimization package. We have a fitness function that is fairly computationally intensive to evaluate and we have a cluster to run this on so parallelized code is highly desirable. So is c++ a good language for this? If not please recommend some other ones as I am willing to learn another language if it makes life easier. thanks!

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• C# Algorithms for * Operator

  - by Harsha

  I was reading up on Algorithms and came across the Karatsuba multiplication algorithm and a little wiki-ing led to the Schonhage-Strassen and Furer algorithms for multiplication. I was wondering what algorithms are used on the * operator in C#? While multiplying a pair of integers or doubles, does it use a combination of algorithms with some kind of strategy based on the size of the numbers? How could I find out the implementation details for C#?

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• Genetic Programming in C#

  - by Mac

  I've been looking for some good genetic programming examples for C#. Anyone knows of good online/book resources? Wonder if there is a C# library out there for Evolutionary/Genetic programming?

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• What is Crossover Probability & Mutation Probability in Genetic Algorithm or Genetic Programming ?

  - by Reddy

  What is Crossover Probability & Mutation Probability in Genetic Algorithm or Genetic Programming ? Please explain them from implementation perspective!

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• I don't understand why algorithms are so special

  - by Jessica

  I'm a student of computer science trying to soak up as much information on the topic as I can during my free time. I keep returning to algorithms time and again in various formats (online course, book, web tutorial), but the concept fails to sustain my attention. I just don't understand: why are algorithms so special? I can tell you why fractals are awesome, why the golden ratio is awesome, why origami is awesome and scientific applications of all the above. Heck I even love Newton's laws and conical sections. But when it comes to algorithms, I'm just not astounded. They are not insightful in new ways about human cognition at all. I was expecting algorithms to be shattering preconceptions and mind-altering but time and time again they fail miserably. What am I doing wrong in my approach? Can someone tell me why algorithms are so awesome?

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• What's a good, quick algorithms refresh?

  - by Casey Patton

  I have programming interviews coming up in a couple weeks. I took an algorithms class a while ago but likely forgot some key concepts. I'm looking for something like a very short book (< 100 pages) on algorithms to get back up to speed. Sorting algorithms, data structures, and any other essentials should be included. It doesn't have to be a book...just looking for a great way to get caught up in about a week. What's the best tool for a quick algorithms intro or refresher?

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• What are the algorithms that are used for working with large data in popular web applications

  - by Moss Farmer

  I am looking for some well known algorithms that can be considered while handling very large amount of data.(Edit- By large amount of data I refer to records in a database excluding blobs). These algorithms if not in totality but in parts may be used in big web applications like Twitter, Last.fm , Amazon ,etc. Specifically, I'm looking for names or links to such algorithms. My primary interest lies in developing a very deep understanding on working with large database records and writing efficient code for working with the same.

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• Do you have genetic algorithm in production?

  - by Max

  Is it good idea to use genetic algorithm in production? If you are using it: In what case? What pros for selecting subj? Can you easily add changes to algorithm?

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• Genetic Programming Online Learning

  - by Lirik

  Has anybody seen a GP implemented with online learning rather than the standard offline learning? I've done some stuff with genetic programs and I simply can't figure out what would be a good way to make the learning process online. Please let me know if you have any ideas, seen any implementations, or have any references that I can look at.

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• Genetic Algorithm new generation exponentially increasing

  - by Rdz

  I'm programming Genetic Algorithm in C++ and after searching all kind of ways of doing GA'a operators (selection, crossover, mutation) I came up with a doubt. Let's say I have an initial population of 500. My selection will consist in getting the top 20% of 500(based on best fitness). So I get 100 individuals to mate. When I do the crossover I'll get 2 children where both together have 50% of surviving. So far so good. I start the mutation, and everything's ok.. Now when I start choosing the Next generation, I see that I have a big number of children (in this case, 4950 if you wanna know). Now the thing is, every time I run GA, if I send all the children to the next generation, the number of individuals per generation will increase exponentially. So there must be a way of choosing the children to fulfill a new generation without getting out of this range of the initial population. What I'm asking here is if there is anyway of choosing the children to fill the new generations OR should I choose somehow (and maybe reduce) the parents to mate so I don't get so many children in the end. Thanks :)

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• Genetic Algorithms applied to Curve Fitting

  - by devoured elysium

  Let's imagine I have an unknown function that I want to approximate via Genetic Algorithms. For this case, I'll assume it is y = 2x. I'd have a DNA composed of 5 elements, one y for each x, from x = 0 to x = 4, in which, after a lot of trials and computation and I'd arrive near something of the form: best_adn = [ 0, 2, 4, 6, 8 ] Keep in mind I don't know beforehand if it is a linear function, a polynomial or something way more ugly, Also, my goal is not to infer from the best_adn what is the type of function, I just want those points, so I can use them later. This was just an example problem. In my case, instead of having only 5 points in the DNA, I have something like 50 or 100. What is the best approach with GA to find the best set of points? Generating a population of 100, discard the worse 20% Recombine the remaining 80%? How? Cutting them at a random point and then putting together the first part of ADN of the father with the second part of ADN of the mother? Mutation, how should I define in this kind of problem mutation? Is it worth using Elitism? Any other simple idea worth using around? Thanks

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• Implementing crossover in genetic programming

  - by Name

  Hi, I'm writing a genetic programming (GP) system (in C but that's a minor detail). I've read a lot of the literature (Koza, Poli, Langdon, Banzhaf, Brameier, et al) but there are some implementation details I've never seen explained. For example: I'm using a steady state population rather than a generational approach, primarily to use all of the computer's memory rather than reserve half for the interim population. Q1. In GP, as opposed to GA, when you perform crossover you select two parents but do you create one child or two, or is that a free choice you have? Q2. In steady state GP, as opposed to a generational system, what members of the population do the children created by crossover replace? This is what I haven't seen discussed. Is it the two parents, or is it two other, randomly-selected members? I can understand if it's the latter, and that you might use negative tournament selection to choose members to replace, but would that not create premature convergence? (After a crossover event the population contains the two original parents plus two children of those parents, and two other random members get removed. Elitism is inherent.) Q3. Is there a Web forum or mailing list focused on GP? Oddly I haven't found one. Yahoo's GP group is used almost exclusively for announcements, the Poli/Langdon Field Guide forum is almost silent, and GP discussions on general/game programming sites like gamedev.net are very basic. Thanks for any help you can provide!

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• test cases for common algorithms [on hold]

  - by Alexey

  I need samples of test inputs and correct outputs for common algorithms for sorting, searching, data structures, graphs, etc. to check for mistakes in my future implementations. Can you advice resources with test cases? Or a website with community that implements algorithms and shares with results? Thanks! Edit: to clarify: I am going to implement forementioned algorithms for studying purposes and need inputs including large ones and correct outputs to better find mistakes in my implementations, since test cases that I can come up with on my own with might not be enough to reveal mistakes.

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• Genetic algorithms with large chromosomes

  - by Howie

  I'm trying to solve the graph partitioning problem on large graphs (between a billion and trillion elements) using GA. The problem is that even one chromosome will take several gigs of memory. Are there any general compression techniques for chromosome encoding? Or should I look into distributed GA? NOTE: using some sort of evolutionary algorithm for this problem is a must! GA seems to be the best fit (although not for such large chromosomes). EDIT: I'm looking for state-of-the-art methods that other authors have used to solved the problem of large chromosomes. Note that I'm looking for either a more general solution or a solution particular to graph partitioning. Basically I'm looking for related works, as I, too, am attempting using GA for the problem of graph partitioning. So far I haven't found anyone that might have this problem of large chromosomes nor has tried to solve it.

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• Initial Genetic Programming Parameters

  - by cmptrer

  I did a little GP (note:very little) work in college and have been playing around with it recently. My question is in regards to the intial run settings (population size, number of generations, min/max depth of trees, min/max depth of initial trees, percentages to use for different reproduction operations, etc.). What is the normal practice for setting these parameters? What papers/sites do people use as a good guide?

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• What Genetic Algorithm/Programming library do you use?

  - by bias

  What GA/GP lib do you use and why?

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• Algorithms and Programmer's day-to-day job

  - by Lior Kogan

  As of July 10, 2012, Stack Overflow contains 3,345,864 questions, out of which 20,840 questions are tagged as "Algorithm" - this is less than 0.6% ! I find it disturbing. Many programmers have several years of academic education in computer science / software engineering. Most of them are smart... When asked, most would say that they love algorithms. Computer programming is generally about solving problems using algorithms... Yet, only 1 of 160 questions is tagged as algorithm related. What does it say about our profession?

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• Easy to understand and interesting book on algorithms

  - by gasan

  Please advise me a book on algorithms, that would be easier to read and understand than Cormen's book1. It may be not so big and deep in explanation. I even want it to not be that big, however it shouldn't contain misconceptions or errors or inaccuracies. It should be a some kind of pre-Cormen's book, that will help later to understand more sophisticated conceptions. A beginner book (but still worth to read). 1 Introduction to Algorithms by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein

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• problems with studying algorithms

  - by rookie

  hello everyone, I'm currently studying computer science at the Institute, and I have some problems with course which is named Algorithms, I've just begun to study it, but I'm already feeling, that I'm going to fail it, my problem is that while understanding different algorithms on graphs I need to keep in my mind a lot of info, and usually I can't do it, I forget some points of the exercise or can't proceed to final result, I'm very desperate about it cause I like programming very much. Did somebody feel the same while studying in the University? thanks in advance for any help P.S. I began to program only two years ago, may it be the problem?

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• Sort algorithms that work on large amount of data

  - by Giorgio

  I am looking for sorting algorithms that can work on a large amount of data, i.e. that can work even when the whole data set cannot be held in main memory at once. The only candidate that I have found up to now is merge sort: you can implement the algorithm in such a way that it scans your data set at each merge without holding all the data in main memory at once. The variation of merge sort I have in mind is described in this article in section Use with tape drives. I think this is a good solution (with complexity O(n x log(n)) but I am curious to know if there are other (possibly faster) sorting algorithms that can work on large data sets that do not fit in main memory. EDIT Here are some more details, as required by the answers: The data needs to be sorted periodically, e.g. once in a month. I do not need to insert a few records and have the data sorted incrementally. My example text file is about 1 GB UTF-8 text, but I wanted to solve the problem in general, even if the file were, say, 20 GB. It is not in a database and, due to other constraints, it cannot be. The data is dumped by others as a text file, I have my own code to read this text file. The format of the data is a text file: new line characters are record separators. One possible improvement I had in mind was to split the file into files that are small enough to be sorted in memory, and finally merge all these files using the algorithm I have described above.

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• Evolutionary Algorithms: Optimal Repopulation Breakdowns

  - by Brian MacKay

  It's really all in the title, but here's a breakdown for anyone who is interested in Evolutionary Algorithms: In an EA, the basic premise is that you randomly generate a certain number of organisms (which are really just sets of parameters), run them against a problem, and then let the top performers survive. You then repopulate with a combination of crossbreeds of the survivors, mutations of the survivors, and also a certain number of new random organisms. Do that several thousand times, and efficient organisms arise. Some people also do things like introduce multiple "islands" of organisms, which are seperate populations that are allowed to crossbreed once in awhile. So, my question is: what are the optimal repopulation percentages? I have been keeping the top 10% performers, and repopulating with 30% crossbreeds and 30% mutations. The remaining 30% is for new organisms. I have also tried out the multiple island theory, and I'm interested in your results on that as well. It is not lost on me that this is exactly the type of problem an EA could solve. Are you aware of anyone trying that? Thanks in advance!

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• Where to find algorithms work?

  - by Misha

  The funnest parts of my projects have been the back-end algorithms work. I have worked on projects where I implemented Gaussian Mixture models, a Remez algorithm and a few Monte Carlo schemes. I loved figuring out how these processes worked and tuning them when they didn't. I recently graduated and my problem lies in the work I was able to find. The only jobs I have found, with my Electrical Engineering degree, are for writing user applications. Tasks such as fashioning web interfaces or front-ends for hardware devices. When I speak with potential employers about my interests they say they have no work of the sort. Where does one find work that involves implementing these kind of schemes?

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