Study of Greedy Genetic Algorithm for Multi-Objective Optimization

摘要

Based on greedy policies, the greedy genetic algorithm (GGA) is proposed for multi-objective optimization problems. In the process of evolution, the greedy policies are used to initialize population, generate crossover and mutation operator, and add new individuals to the population every a few generations. All these procedures are designed to prevent premature convergence and improve the performance of Pareto front,which can be showed by examples of six test functions.