Genetic Algorithm Path Planning Program for Solving Shortest Path Problems

This MATLAB-implemented genetic algorithm path planning program solves shortest path optimization problems. The program utilizes genetic algorithms to find optimal paths and can be applied to various problem domains. Genetic algorithms mimic natural evolutionary processes by simulating genetic inheritance and mutation mechanisms found in biological evolution. Through iterative optimization cycles involving selection, crossover, and mutation operations, the algorithm progressively converges toward optimal solutions. Key implementation features include chromosome encoding of path sequences, fitness evaluation based on path length calculation, and genetic operators for population evolution. The MATLAB code typically incorporates functions for population initialization, fitness computation, tournament selection, crossover operations (such as ordered crossover for path preservation), and mutation mechanisms. This approach enables effective shortest path solutions across diverse application scenarios, significantly improving computational efficiency and solution accuracy compared to traditional methods.