# 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.

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### Measuring and maintaining the diversity of individuals in Genetic Algorithm

While I was using the Genetic Algorithm to generate full correct Sudoku grids starting from a population of random grids, I occasionally face the problem of the process being stuck on a local maxima ...
890 views

### NeuroEvolution: NEAT algorithm innovation numbers

I have been reading up on the NeuronEvolution of Augmented Topologies and there's this little thing that's been bothering me. While reading Kenneth Stanley's Paper on NEAT I came on this figure here: ...
94 views

### Direct encoding of the solution into the chromosomes in a Random-Key Genetic Algorithm

In a random key genetic algorithm1, the chromosomes consist in a sequence of real numbers (initially randomly generated) in the interval $[0,1]$. I've been told by my teacher that in these kinds of ...
342 views

### It's necessary to replace all the population each generation in a genetic algorithm?

I'm creating a timetable generator using GA's, and I'm stuck in the crossover part. Each generation, I just basically copy the best individuals (the 50% fittest individuals inside the population), ...
45 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 ...
49 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 ...
75 views

### Is my implementation of genetic algorithm correct?

In genetic algorithms, we have a function called "mutation". Before we call this function, we choose parents. In my version of the algorithm, when i mutate the child, i don't change the bits which ...
572 views

### Pittsburgh approach, how does encoding and fitness function work?

I am writing a genetic algorithm for Machine learning and came across Pittsburgh approach in some research papers. The papers didn't explain the algorithms proper or I am too stupid to understand. I ...
556 views

### What crossover operator should I use for arranging students in classrooms?

I am building a genetic algorithm to solve a "classroom map" problem. The goal is to place correctly students depending on several factors (shortsighted students, turbulent students...). Here, the ...
55 views

### Measuring Fitness in Genetic Programming Functionology

I recently begun working on a genetic algorithm to solve for patterns in data. More specifically, it solves for functions given a sample of ins and outs. So a possible solution would be X+2 = Y. The ...
5k 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, ...
296 views

### Does local optimization in a genetic algorithm decrease diversity?

I want to create a hybrid genetic algorithm for a project to solve really high dimensional problems (1000+) One of my ideas is to incorporate a local optimization method within GA so each individual ...
594 views

### Should you use Genetic algorithm for an extremly large unstructured search space?

My search space is discrete and in the order of $10^{1360}$, with a probably very complex fitness surface. Is it hopeless to attempt to use GA for such a problem? One fitness evaluation could take 1-3 ...
243 views

### Variation of rank selection in genetic algorithm

I'm looking for a specific variation of rank selection in genetic algorithms. I came across a python program tailored for a specific problem that uses a variant of "rank" selection. In normal rank ...
79 views

### Genetic Algorithms: Converge to best solution for one, few or many environments?

Let's say we take someone's garden (A) as the environment. We want a robot to pick up a series of eggs that chickens have laid in the garden, while covering as little ground as possible (those heavy ...
80 views

### Can the reproduction function of an evolutionary algorithm consider gene strength?

I am trying to solve the Zen Garden puzzle using an evolutionary algorithm. My question relates to evolutionary algorithms in general. Bit about evolutionary algorithms: An evolutionary algorithm is ...
204 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 ...
89 views

### Fitness functions for low-dimensional parts of cooperative coevolution algorithms

In cooperative coevolution algorithms, a high dimensional vector is broken into smaller vectors, each of which is optimized separately using EAs for fewer dimensions and then recombined. What is the ...
2k views

### Train a neural network to play tic tac toe using a genetic algorithm

I have an assignment for school, in which I have to build a neural network that will play tic tac toe, using genetic algorithms for training. The thing is that I am clueless on how to connect the two. ...
3k views

### Genetic Algorithms - Tournament Selection

I know this should be a fairly simple concept but I have been Googling a lot and can't seem to find a definitive definition. If we had the following random population: ...
295 views

### Genetic Algorithms - Why wouldn't we use the principle of Elitism?

In Genetic Algorithms, the idea of elitism is that we keep our best solution from the generation in our population regardless of what happens throughout the iteration. However, elitism seems to be ...
3k views

### How to identify when to use Genetic Algorithm/Programming

I have been reading/studying on genetic algorithm/programming, and have implemented Traveling salesman problem. TSP is basically a permutation/combination problem, and I can understand how GA helps ...
644 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) ...
16 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 ...
584 views

### How do genetic algorithms work exactly?

I was looking at the basic genetic algorithm here http://www.ai-junkie.com/ga/intro/gat1.html But I have some questions about things I didn't get. To reiterate: You have a problem you want a good ...
2k views

### Is Differential Evolution a genetic algorithm?

I am trying to classify the Differential Evolution algorithm according to the framework in the book: Introduction to Evolutionary Computing The authors classify the field of evolutionary ...
59 views

### Comparing different implementations of genetic algorithms

I am looking up some material for my thesis in CS (development of a module to integrate a genetic algorithm in a system developed by other students). My actual current task is to make a comparative ...
4k views

### Evolving artificial neural networks for solving NP problems

I've recently read a really interesting blog entry from Google Research Blog talking about neural network. Basically they use this neural networks for solving various problems like image recognition. ...
2k 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, ...
85 views

### Programming a genetic algorithm with a non-fixed size

I am trying to write a genetic algorithm for a program. Most examples for genetic algorithms use something like this as the input: aaaaaaaaaa and mutate/...
197 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. ...
1k views

### Disadvantages to using simple step functions for activation in neural networks?

From what I have read, the main advantage to using tanh(x) or sigmoid(x) as an activation function for neural networks is that it is very easily differentiable. I am trying to implement a neural ...
811 views

### Why are syntax trees used in genetic programming?

Reading a course on genetic programming, the first chapter describes the syntax tree as the basic representation of programs in genetic programming. What are the reasons leading to the choice of a ...
2k views

### TSP genetic algorithm: what mutation function for adjacency representation?

When implementing TSP GA I decided for adjacency representation (i.e. $j$ value in $i$-th index means that node $j$ goes right after node $i$), as it enables interesting heuristical crossover ...
99 views

### A clarification on the taxonomy of Evolutionary Algorithms

A rather basic question but I am confused about the characterization of a certain local search method which I want to describe in the framework of EAs. In particular, consider an EA which in every ...