A genetic algorithm is an optimization heuristic that is inspired by the principles that drive natural evolution: mutation, recombination and selection. In comparison to traditional search methods such as hill-climbing, genetic algorithms have the ability to escape from local minima/maxima.
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Genetic algorithm implementation
Is this the best way to implement a genetic algorithm framework? I'm just a student and wanted to know if I can improve the code that I have done. Some of the code I copied from the framework ...
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Genetic algorithm in Java
I am working on a genetic algorithm using the following code. The variable best in generateNewPopulation stores the best ...
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Haskell Non-Dominated sorting
This algorithm sorts a list of Individuals, each with two fitness values, into what's called non-dominated fronts. A non-dominated front is a set of individuals where none of the individuals dominate ...
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Genetic algorithm to find the maximum binary number of a given length
I have written some codes in java implementing simplest genetic algorithm. The code finds (or rather tries to) the maximum value possible for a user-defined number of bits. For example, for 16 bit ...
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Performance optimization when switching from nested to flat representation (genetic algorithm)
The code below is the core of a Genetic Algorithm (NSGA-II to be precise, without crowding-distance calculation), but I've taken out all the GA-specific parts and made a generic example. I think I've ...
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Genetic algorithm to arrange rooms in a house
I am an architecture thesis student in my final year and I am developing a piece of software that, ideally, should design houses for me based on certain input.
I got the program to work when it was ...
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Hash Matrix performs Gaussian elimination
This is the Hash-Matrix that I used in order to process the matrix for my quadratic sieve algorithm. You can find the full code at here(it's java 7), but I only want you to review this class.
My ...
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Travelling Salesman problem using GA, mutation, and crossover
I created a short python program that can create a list of random unique nodes with a given length and a given number of strategies. The GA runs through a given number of generations, changing a ...
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Evolutionary algorithm to optimize the range of a glider
I created an evolutionary algorithm that optimises the range of a "glider"...ignore the accuracy of the physics behind the problem!
Any comments on how to improve the algorithm/my coding style would ...
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Alberi creator. Keepalive
This post is a follow-follow-up to this post and its follow-up.
In those two posts we managed to speed-up the solution of an Alberi puzzle, and to create a one-tree-per-region puzzle.
The complete ...
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624 views
Genetic algorithm to fill timetable for school
I wrote a program to fill a timetable for a school. There are some simple rules:
Each subject has a preset number of blocks (blocks are 2 hour periods).
Professor provide a valid hours they have ...
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PMX crossover implementation in Clojure
I'm starting to learn Clojure and as an exercise I've implemented the following functions (written in Java) in Clojure:
...
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Genetic search algorithm for TSP
I made a genetic search algorithm in Python for the Travelling Salesman Problem for a midterm project. The grade was fine, but I was hoping to get some pointers on style and documentation. Please ...
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Neural Net XOR Genetic Algorithms
New to Neural Networks and before I move on to gradient descent I would like to make sure I have got basic idea right. (Sorry that the class is called perceptron I know that this isnt technically ...
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Genetic algorithm final stage
I have written the code for a genetic algorithm and have the crossover function, mutation function, parent selector function and a function to transfer genes. Now I want to put it all together and ...
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Genetic Drift Simulator - Follow Up
This question is a follow-up of a previous question of mine: Genetic Drift Simulator.
Following the advice given in the last question, and some more general improvements, the code has been slimmed ...
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Genetic Drift simulator
Genetic drift — along with natural selection, mutation, and migration — is one of the basic mechanisms of evolution.
In each generation, some individuals may, just by chance, leave behind a few ...
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Backpropagating with Neural Network
I wrote a Java program implementing a neural network with backpropagation. For anyone who isn't familiar with Neural Networks and Backpropagation, here is a good resource. Here is another ...
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Genetic Algorithm for TSP
This is something that I am proud of and would like to have people dissect and tell me where my faults are in. I feel that if I open my best for criticism then maybe it will reveal the deep seeded bad ...
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Genetic algorithm for solving a puzzle (v. 2)
Thanks to your wonderful comments regarding the first version of my code, I have been able to improve it. This new version is more readable (I guess). The problem is that it seems to me that there is ...
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Genetic algorithm for solving a puzzle
Edit. Version 2.
I am working on a genetic algorithm in order to solve a little "puzzle."
Given a text file with N rows with 4 int each, the idea is to ...
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Genetic algorithm for “Hello World”
This programme uses a genetic algorithm to get the string "Hello, World!". It can be summarized as follows:
Create a random initial population.
Let the best ...
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Where equations are born and mutants are buried
I've read up on genetic programming yesterday so I figured I'd try to implement something myself. I would like the main focus to be on whether or not I've implemented the idea behind it correctly.
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Genetic algorithm for “Hello World”
I've written an Erlang implementation of the genetic algorithm for a "Hello World" program as described here.
This is my first time writing any code in Erlang and also my first time writing code in a ...
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Genetic algorithm for Clever Algorithms project
I wrote a bunch of Ruby code for a book project I've just finished. One criticism is that it is fine code but not very "ruby like". I agree my style was simplified for communication reasons, and ...
