Genetic Algorithm Solution for CARP (Directed Multi-Chinese Postman Problem)

This article presents a genetic algorithm solution for CARP (Directed Multi-Chinese Postman Problem) featuring flexible modification of objectives and constraints. The implementation utilizes the University of Sheffield Genetic Algorithm Toolbox, which must be installed beforehand. Before employing the toolbox, users can customize the solution by modifying objective functions and constraint handling mechanisms through parameter adjustments in the fitness function and constraint validation modules. The algorithm employs chromosome encoding to represent route sequences, with specialized crossover and mutation operators designed for path optimization. Key functions include population initialization with feasible routes, elitism selection for preserving best solutions, and penalty methods for constraint management. This approach allows researchers to adapt the algorithm for various CARP variants by simply adjusting the evaluation criteria and constraint checks in the core optimization loop.