Skip to main content

Questions tagged [genetic-algorithms]

Questions on genetic algorithms, a family of evolutionary search heuristics. Genetic Algorithms are adaptive heuristic search algorithms based on the evolutionary ideas of natural selection and generics.

43 questions with no upvoted or accepted answers
Filter by
Sorted by
Tagged with
4 votes
0 answers
147 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 ...
guestrest's user avatar
3 votes
1 answer
382 views

Difference between selecting a large pool of individuals for reproduction, and selecting two parents specifically

I have implemented a genetic algorithm for an optimization problem and I'm now trying to improve it to see if I can find better solutions or faster convergence. I am confused about the selection part ...
Nick Thissen's user avatar
3 votes
0 answers
114 views

Are there are satisfying explanations for why genetic algorithms work?

The following commentator writes: Having studied this extensively back when they were called Genetic Algorithms, I would like to offer a few insights. One of the biggest reasons they fell out of ...
hawkeye's user avatar
  • 1,199
3 votes
0 answers
2k views

Genetic algorithm crossover technique for solving graph colouring problem

I am trying to develop a genetic algorithm to solve a graph colouring problem. The problem is the standard graph colouring problem, given a graph $G = (V,E)$ where $V$ is the set of vertices $V=\{0 \...
guskenny83's user avatar
2 votes
1 answer
59 views

EvoPathfinding - Stuck in local optimal

I am using a Genetic Algorithm framework to solve a path-finding problem. Specifically, given the following 32x32 maze: ...
ex1led's user avatar
  • 121
2 votes
0 answers
31 views

genetic algorithm with different categories of parameters

I am trying to use a genetic algorithm to solve a problem. However, I find it difficult to represent the chromosomes in my problem. In the problem, I have two categories of parameters, and each gene ...
Noon's user avatar
  • 21
2 votes
1 answer
2k views

Using 2-opt Heuristic in a Genetic Algorithm for TSP

I read few papers while trying to find some better approachs to solve the TSP (Traveling salesman problem) as close to the optimal solution as possible. I implemented a Improved Greedy Crossover (...
Haytam's user avatar
  • 123
1 vote
0 answers
59 views

Mutation probability on strongly varying chromosome length

I am working on a Genetic (or rather Memetic) Algorithm for optimizing a scheduling problem. I have n orders to schedule and the solution representation is an array of n integers that specify when an ...
Patrick Malik's user avatar
1 vote
0 answers
70 views

How to choose the initial temperature in the Boltzmann selection method?

Using the Boltzmann selection in genetic algorithms, the probability of visiting a point in optimization space $X_j$ is $p(X_j)=\frac{\exp\frac{-f(X_j)}{T}}{\sum_i \exp \frac{-f(X_i)}{T}}$ my question ...
imaima's user avatar
  • 11
1 vote
0 answers
32 views

Dynamic Chromosome Length in Genetic Algorithms

My inquiry concerns the length of chromosomes employed in genetic algorithms (GA), and more broadly in other classes of evolutionary algorithms. The chromosome length is fixed throughout a GA's run. ...
compbiostats's user avatar
1 vote
0 answers
26 views

Repair operator for evolutionary algorithm

I am working on a resource allocation problem using an SPEA 2 evolutionary algorithm. The problem involves decision variables where each variable has a different domain e.g. $E_i \le d_i$ where $E_i$ ...
user76646's user avatar
1 vote
0 answers
23 views

Crossover method for 3D velocity vector genetic algorithm

I am trying to write a genetic algorithm which will learn how to throw a ball at a target. I have successfully implemented code that will graph the projectile motion of a sphere given an input ...
F J's user avatar
  • 11
1 vote
0 answers
44 views

The number of samples in SUS selection method

In stochastic Universal Sampling selection method of genetic algorithm, the number of selected samples is usually static. I wanted to know if it is possible to select the number of these samples ...
helen's user avatar
  • 111
1 vote
0 answers
206 views

Genetic programming - tournament selection and elite

I am writing a thesis about automatic GUI testing. In order to find the fittest strategy I am using GP. I am using tournament selection to select chromosomes for the next generation and elitism to ...
GuyT's user avatar
  • 111
1 vote
0 answers
40 views

How to improve convergence to an equilibrium value, & damp oscillation?

I am developing a program which seeks strategies for the players A, B in any of a family of simple 2-player gambling-games. The program iterates, using a genetic algorithm to determine, from the ...
Rosie F's user avatar
  • 111
1 vote
0 answers
62 views

Generate a random tree population

Given a unbalanced k-ary tree base (with internal nodes that represent operators and leafs representing values) from the space of all unbalanced k-ary trees ...
Lorenz's user avatar
  • 11
1 vote
1 answer
134 views

Choosing Fitness function for float output in Genetic algorithm

I have a NN that has ten outputs. The output values range between 0 and 1. The elements in the target array are all zeros except one element, which is "one". I am searching for a Fitness Function ...
Max Z's user avatar
  • 11
1 vote
0 answers
146 views

Chromosome length in Genetic Algorithms

In order to find the appropriate length of chromosomes in GA programming, the author of this book states: Suppose six decimal places for the variables' values is desirable. It is clear that to ...
RezAm's user avatar
  • 111
1 vote
0 answers
72 views

Unknown length of chromosone in genetic algorithm

I've read some about genetic algorithms and the general approach, but I haven't found anything about using it when the length of the solution is unknown. How would the generation of the initial ...
Ferus's user avatar
  • 143
1 vote
0 answers
188 views

adjusted fitness in NEAT algorithm

I'm learning about NEAT from the following paper: http://nn.cs.utexas.edu/downloads/papers/stanley.ec02.pdf I'm having trouble understanding how adjusted fitness penalizes large species and prevents ...
wonder's user avatar
  • 11
1 vote
0 answers
135 views

Genetic Algorithm for maximization

this may be a shot in the dark, but I am trying to teach myself more machine learning concepts. I have found a textbook and am trying to work through the exercises in it. Could anyone help me with ...
Johnny's user avatar
  • 31
1 vote
0 answers
18 views

What use does the predictor stage in a particle filter have?

Im a bit confused about the particle filter. I understand the generic particle filter algorithm but in some literature say particle filter has predictor stage which is not mentioned in the generic ...
Minh Nguyen's user avatar
1 vote
0 answers
1k views

Improving MSE as fitness function for a genetic algorithm

I am implementing an autoencoder neural network in matlab, the weights of which are being optimised by a genetic algorithm. At the moment I am working on the first layer, trying to get an improved ...
guskenny83's user avatar
0 votes
1 answer
45 views

GA/GP subtree crossover/mutation with all items present?

I have a genetic algorithm/programming problem where I need the best arrange of items in a binary tree. My question is the best way to mutate/cross this binary tree subject to constraints described ...
Ana's user avatar
  • 21
0 votes
0 answers
213 views

Solving graph coloring problem using genetic algorithms

I have some basic information about the graph coloring problem, which is an NP-Complete problem. I am very new to genetic algorithms, and I have faced a problem in which we have to solve the graph ...
Aylin Naebzadeh's user avatar
0 votes
0 answers
19 views

How to plot the 'back-to-home-city-path' in TSA without repeating cities

I'm doing an implementation of the traveling salesman problem using genetic algorithms, but I can't get it: If we need to get the best route in a certain set of cities and then go back to the first ...
deniable_encryption's user avatar
0 votes
0 answers
46 views

Genetic algorithm, transformation methods for the different objective function

I am using a genetic algorithm for the optimization of a thermodynamic cycle. The problem has no analytical solution and the solution space is computationally large. The question is the following: How ...
Panus Kladus's user avatar
0 votes
0 answers
26 views

How to mix populations in multi population genetic algorithm?

I'm working on an optimization problem using genetic algorithm. To increase diversity of potential solutions I'm using multi-population approach: Instead of evolving one population I run 10 ...
PanJanek's user avatar
  • 101
0 votes
0 answers
139 views

Travelling Salesman Problem: Distance between solutions

I'm designing a genetic algorithm to solve the travelling salesman problem. So far, I've gotten fairly good results. I'm now trying to improve on them by implementing some sort of diversification ...
Inkidu616's user avatar
  • 101
0 votes
0 answers
22 views

Duplicate dominating parents when using Deterministic Crowding in Genetic Algorithm

This is the pseudocode for using deterministic crowding: ...
Moons's user avatar
  • 101
0 votes
0 answers
35 views

Find consensus trajectory of how a genetic algorithm solves an optimization

I have implemented a genetic algorithm to find the evolutionary outcomes of a biological scenario. I simulate the evolution (i.e. optimization) of five traits in my model. I ran my code 100 times and ...
Armin Dadras's user avatar
0 votes
0 answers
148 views

Number of Times to Run an Evolutionary (Genetic) Algorithm

Evolutionary algorithms like genetic algorithms (GAs) are typically run multiple times and the outputted results are averaged across successive runs. However, in the case of long-runtime algorithms (...
compbiostats's user avatar
0 votes
0 answers
79 views

What kind of standard deviation must be used in optimization algorithms?

I would like to ask about the standard deviation of objective function value. There are two types of standard deviations: Population standard deviation Sample standard deviation In metaheuristic ...
kylo 's user avatar
0 votes
0 answers
64 views

Crossover topologically identical neural networks

I have recently learned about artificial neural networks (very interesting) and genetic algorithms (also very interesting). I have read some suggestions concerning how to crossover two parent neural ...
nc404's user avatar
  • 111
0 votes
0 answers
270 views

How to find the best parameters of a Genetic Algorithm applied to the TSP problem?

I have an assignement where I need to use a Genetic Algorithm to solve the TSP (Traveling Salesman Problem). I alrerady implemented a solution in C# but the problem is we're asked to use some kind of ...
Haytam's user avatar
  • 123
0 votes
0 answers
34 views

Evolutionary Algorithm and Correlation

Note: Not sure with the tags. I'm quite new to this area of Computer Science. I was used to just developing software and applications and applying certain algorithms when necessary. However, I am ...
Kawamoto Takeshi's user avatar
0 votes
0 answers
190 views

Optimization of coefficients by using genetic algorithm

I want to optimization the coefficient of FIR filter using genetic algorithm method. The main data structures in the Genetic Algorithm are: chromosomes (vector) objective function values fitness ...
K.n90's user avatar
  • 13
0 votes
0 answers
40 views

Appropriate optimization algorithm for constraints having NaN values

I am trying to solve a problem where some of the constraints have NaN values. Which algorithm can be used to handle this kind of problem. In my example I have 3 nonlinear inequality constraints, C(1)&...
user avatar
0 votes
0 answers
66 views

Handling eqaulity constraints in genetic algorithms

I am trying to solve an optimization problem with strength pareto algorithm (SPEA2). My decision variable have lower and upper bounds as well as an equality constraint (sum(dp) = 1). I am unable to ...
Saifullah Khalid's user avatar
0 votes
0 answers
68 views

Using Genetic Algorithms for volatile problems

Suppose I am looking at an optimization problem with a large number of interconnected constraints, but the solution is - in some regions - extremely volatile (With volatile I mean: small mutations ...
Radical's user avatar
  • 101
0 votes
0 answers
52 views

Genetic algorithms, Pittsburg - Reach a decision from a set of rules

Consider a binary classification problem. In the Pittsburg approach each member of the population represents a set of rules. Each rule encodes information regarding the data features (that is, the ...
iglesias's user avatar
0 votes
0 answers
242 views

Why does my Genetic Algorithm not work for higher number of individuals?

I am using a cooperative coevolutionary genetic algorithm, the algorithm is given in A cooperative coevolutionary approach to function optimization by DeJong et. al. (1994), for optimizing a 62 ...
Leela Prabhu's user avatar
-1 votes
1 answer
90 views

Genetic algorithm problem

This is a problem I found in an old exam in my school. I have to solve this Genetic Algorithm problem: N students $x_{1},..,x_{N}$ have answered a quiz of 10 questions (True or False questions) and ...
Ahmed Cheikh's user avatar