Genetic algorithm applied to TSP

by

Genetic Algorithms (GAs) are a type of evolutionary algorithm inspired by natural selection, used to find approximate solutions to optimization and search problems. They start with a population of randomly generated candidate solutions, each represented by a chromosome. Individuals are selected based on their fitness, which measures how good a solution is. Selected individuals undergo … Read more

Application of Particle Swarm Optimization Algorithm

by

1.1 Introduction to Particle Swarm Optimization Particle Swarm Optimization (PSO) is an optimization algorithm based on swarm intelligence, inspired by the foraging behavior of bird flocks. Proposed by Kennedy and Eberhart in 1995, it is primarily used to solve optimization problems in continuous spaces. PSO simulates the movement of individuals (particles) within a bird flock … Read more

Genetic algorithms applied to optimize functions.

by

Introduction Genetic algorithms are an optimization algorithm that simulates the natural evolutionary process. By simulating operations such as inheritance, crossover, and mutation, they gradually optimize the solution to a problem. It is derived from the understanding of Darwin’s theory of evolution and the inspiration of Mendelian genetics, and is a meta-heuristic algorithm based on population … Read more

Traveling Salesman Problem (TSP): Exploring from Classical to Intelligent Optimization Algorithms

by

Introduction The Traveling Salesman Problem (TSP) is a classic combinatorial optimization problem that aims to find the shortest path allowing a traveling salesman to visit a series of cities and return to the starting point. This problem has a wide range of practical applications, such as logistics distribution, circuit board wiring, and aerospace fields. The … Read more