Questions tagged [genetic-algorithms]
A genetic algorithm is a class of adaptive stochastic optimization algorithms involving search and optimization. Genetic algorithms were first used by Holland (1975).
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Use PGO (profile guided optimization) to determine optimal value of variables in code
Reading this interesting paper it seems that a lot of performance loss is due to scheduling overhead in tight loops. To recap: There's a variable called "Chunksize" which determines how big ...
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Design problem in C++
I am trying to engineer a library for the Genetic Algorithm optimization method.
The main class for the GA is quite general. Here is what I have for it
struct GAOptions{
size_t max_ga_steps;
...
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Mentorship schedule matchmaking algorithm
A while ago, I tried to help a fella to develop a mentorship matchmaking program given the answers of a questionnaire to match mentors and mentees according to their respective skills and available ...
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Algorithm for rule-based sorting?
I am trying to plant a garden. Certain plants are good for some plants and bad for others, and I am trying to find the best order of plants: most adjacent friends and no adjacent foes, as defined in ...
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Fitness Function altenatives in Genetic Algorithms for game AI
I have created a Gomoku(5 in a row) AI using Alpha-Beta Pruning. It makes move on a not-so-stupid level. First let me describe the grading function of the Alpha-Beta algorithm.
When it receives a ...
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Test Driven Development for Stochastic algorithms?
this is similar, but no the same as this post, which was the closest question I could find on this. I don't even see that answer as satisfactory for the question asked in that thread let alone TDD. ...
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Spreading objects in bags and bags' compartments
We have 10 bags. Each bag has 5 compartments numbered from 1 to 5. We have 100 objects to fill all the compartments and bags.
Compartment number x in a bag is identical to compartment of the same ...
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Dynamic Scheduling Algorithm
Recently I got interested in scheduling problems or rather dynamic scheduling problem. The problem is that I want to develop some kind of layer in my application which will be polling circa about 50-...
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Why do we use binary encoding when it seems so inefficient?
When encoding our chromosome's characteristics (for want of a better word), binary seems to be the favoured method. I understand that this gives the maximum possibilities for crossover and mutation, ...
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How does the genetic algorithm know when to stop if the global minimum isn't known?
Say I'm writing a GA to solve the travelling salesman problem. I don't know in advance what the shortest path is, so how does my GA know when to stop?
If I wait until the best fitness doesn't reduce ...
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How do you encode the genes when you don't know the length?
I think I've got the hang of writing a GA when you know the number of genes in a chromosome. For example, if you're searching for a string, and you know the length, you can just generate your initial ...
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Why do my GAs take so long to converge?
I know GA questions are often almost impossible to answer exactly, but I'm looking for some general advice (although specific advice would be great too!).
I've just written my second GA, which tries ...
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Why have a crossover value that isn't 0.5?
Most of the literature I've read about GAs suggests using a crossover value of around 0.7, so you take the first 70% of one chromosome's genes, and the last 30% of the other to produce one new ...
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How do we produce the next generation?
Thanks to some great replies in a previous question, I think I now have a better understanding of GAs, but am still confused on a couple of points. I'll start with one here.
I've been reading around ...
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How do we know that the next generation will be better?
I was introduced to genetic algorithms recently by this MSDN article, in which he calls them combinatorial evolution, but it seems to be the same thing, and am struggling to understand how combining ...
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