Publication

A dynamic fuzzy-based crossover method for genetic algorithms

2007
Conference Papers

Abstract

Currently, Genetic Algorithms (GA) are widely used in different optimization problems. One of the problems with GAs is tuning their parameters correctly as they can have a significant effect on GA's overall performance. Till now, different methods have been proposed for fine tuning these parameters. Many of these methods use fuzzy linguistic rules in order to find the correct parameters in each stage of the GA evolution. But these methods look at each chromosome as a whole solution for a specific problem. In our contribution, a new method has been proposed which breaks each chromosome into sub parts and uses the better sub-solutions as the building blocks of the next generation using a fuzzy-based approach. The performance of this algorithm has been shown on the Traveling Salesman Problem (TSP) with comparison to Simple GA and Adaptive GA.

Official source

https://infoscience.epfl.ch/entities/publication/d401888c-6529-4ead-8dc0-a1dca3635285

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2007
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/d401888c-6529-4ead-8dc0-a1dca3635285

About this result

Related concepts (32)

Genetic algorithm

In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems by relying on biologically inspired operators such as mutation, crossover and selection. Some examples of GA applications include optimizing decision trees for better performance, solving sudoku puzzles, hyperparameter optimization, causal inference, etc.

Fuzzy control system

A fuzzy control system is a control system based on fuzzy logic—a mathematical system that analyzes analog input values in terms of logical variables that take on continuous values between 0 and 1, in contrast to classical or digital logic, which operates on discrete values of either 1 or 0 (true or false, respectively). Fuzzy logic is widely used in machine control. The term "fuzzy" refers to the fact that the logic involved can deal with concepts that cannot be expressed as the "true" or "false" but rather as "partially true".

Optimization problem

In mathematics, computer science and economics, an optimization problem is the problem of finding the best solution from all feasible solutions. Optimization problems can be divided into two categories, depending on whether the variables are continuous or discrete: An optimization problem with discrete variables is known as a discrete optimization, in which an object such as an integer, permutation or graph must be found from a countable set.

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A dynamic fuzzy-based crossover method for genetic algorithms

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