MATLAB Implementation of VRP Genetic Algorithm

This VRP Genetic Algorithm MATLAB implementation is highly recommended for its comprehensive approach to solving vehicle routing problems. The code provides an effective optimization framework for delivery scheduling and route planning, utilizing genetic algorithm operations including selection, crossover, and mutation to evolve optimal solutions. Key implementation features include population initialization with feasible routes, fitness evaluation based on total distance and constraints, and elitism preservation for convergence stability. The code contains detailed comments explaining each algorithmic component, such as chromosome encoding representing vehicle routes, constraint handling for capacity and time windows, and parameter configuration for evolutionary processes. You can customize the algorithm parameters including population size, mutation rate, and termination criteria to adapt to specific problem requirements. Whether for academic research or industrial applications, this implementation serves as a valuable resource for understanding and applying metaheuristic optimization to logistics problems. The code structure facilitates easy modification for different VRP variants, demonstrating practical genetic algorithm implementation techniques with clear separation of initialization, evaluation, and evolutionary operators.