Questions on genetic algorithms, a family of evolutionary search heuristics.

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2
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1answer
67 views

How to stop genetic algorithm population converging to a single value

I've written a genetic algorithm (GA) that solves a 7-dimensional optimisation problem. All seven variables are floating point numbers. The problem is that the entire population seems to converge to ...
0
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0answers
26 views

Does using diploid (dominant/recessive) genes in genetic algorithm offer any advantage? [duplicate]

I've been looking into diploid genetic algorithms for a while. Although, it seems like an implementation which includes diploid (dominant/recessive) genes is closer to the implementation that has ...
2
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1answer
47 views

Genetic algorithm fitness function [closed]

I'm trying to write some little code (POC for the selection/mutation operators) that uses a genetic algorithm to solve a global maximum for a function. ...
11
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1answer
39 views

Why are diploid (dominant/recessive) genes not used widely in genetic algorithms?

In most implementations of genetic algorithms, the focus is on crossover and mutation. But somehow, most of them leave out diploid (dominant/recessive) nature of genes. As far as my (limited) ...
8
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2answers
16 views

Selection of parameters for genetic algorithm

How can one select the proper number of parameters for a genetic algorithm to model a given system? For example, say you want to optimize production of cars, and you have 1,000 measurements of hourly ...
3
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2answers
72 views

Computer Music Composition

I've been looking into computer assisted music composition lately for my school project. While searching for literature I came across GenJam, an interactive jazz improvisation software which uses ...
3
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2answers
80 views

Genetic algorithm: What is the expected number of strings that are explored?

My question concerns genetic algorithm searching along bit strings. Given: $N$ = population size $l$ = length of bit strings $p_c$ = probability that a single crossover occur (double crossover ...
2
votes
1answer
90 views

How to analyze the performance of a genetic algorithm experimentally?

I have a genetic algorithm for an optimization problem. I plotted the running time of the algorithm on several runs on the same input and the same parameters (population size, generation size, ...
2
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3answers
99 views

A genetic algorithm modified for a specific problem

I have a problem whose solution can be written as a binary string with a given length $N$, where $N$ is a given parameter. Standard GA works well on this problem. From runs of small values $N$, I ...
1
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0answers
57 views

Crossover method for genetic algorithm

I got an amount of numbers, they are shuffled and represent the individuals. For example (3,1,3,2,5,22,5) is one individual or (22,3,1,3,5,5,2). Mutation is done quite easy by permutation within an ...
2
votes
1answer
139 views

How to use Sigma Scaling in a genetic algorithm

I have a genetic algorithm in Java and I'm testing new types of selections. For my tests I'm using the De Jong Half Sphere, my fitness function is $x^2 + y^2$. The selection method used is Sigma ...
0
votes
1answer
26 views

Is there a crossover operator to cross sections of specific phenotype genes?

For example, I've a chromosome with 10 genes, the first 5 genes represent a specific property of phenotype and the last 5 genes represent another property of phenotype. So, I need a crossover ...
4
votes
1answer
105 views

Something I don't understand about Genetic Algorithms

I've had a bit of experience programming Neural networks but I am fairly new with genetic algorithms (I'm only 17). I have a major issue that I can't understand. If a child get's one chromatid from ...
2
votes
1answer
232 views

Classification of job shop scheduling problems

I'm writing a program (using genetic algorithms) that finds sort-of-optimal scheduling plan for a factory. The factory has several types of machines (say, ...
1
vote
3answers
264 views

Standard Parameters for Genetic Algorithms

I'm currently writing my thesis, which uses genetic algorithms at some point. Now I need to define some parameters for the genetic algorithm I know that, because of the No Free Lunch Theorem there ...
2
votes
1answer
54 views

Evolutionary algorithm - how to select the parents

I try to solve Physical Travelling Salesman Problem using evolutionary algorithm and I have diffucult to detemine how to choose the parent , on which we do the crossover. Assume I have popultion of ...
1
vote
1answer
119 views

Evolutionary algorithm for the Physical Travelling Salesman Problem

I want to solve the Physical Travelling Salesman Problem using an evolutionary algorithm. The objective of the PTSP is to visit the maximum number of waypoints of the map in the minimum number of ...
1
vote
1answer
107 views

Are genetic algorithms special instances of random search done in an unexpectedly short run-time? [closed]

I was wondering since randomness is embedded in genetic algorithms at almost every level, is there a really fine line between genetic algorithms and pure random search? Ever since I finished my ...
4
votes
0answers
40 views

Stochasticity of Genetic Algorithm

I have a set of observations of real data, and a set of Random Variables I produce my self. The goal is to generated Random Variables with the same Distribution as the real data. To investigate the ...
3
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0answers
62 views

Lamarckian and Genetic algorithm

Yesterday I've done some research how to optimize genetic algorithm and I've encountered a very interesting theory that we can use Lamarckian theory (adaptive theory) to optimize the neural network. ...