An Application of Agent-based Multi-Objective Genetic Algorithm

An Improved Agent-Based Genetic Algorithm is used to solve the multi-objective Network Optimization Problems. The Agent is used to the genetic algorithm and the specific encoding is used to encode the path of network. The Pareto competition classic ordering method is used for the calculation of Agent energy. The partial mapping crossover is used to deal with the conflict of genes in crossover process. Comparative experiments show that the algorithm is efficient when is used to solve network multi-objective optimization problems.