摘要
蚁群算法和遗传算法都属于仿生型优化算法,是解决调度问题的强有力的工具。本文针对多目标车间调度问题提出了一种多种群蚁群算法和遗传算法想结合的算法,算法的第一部分用多种群蚁群算法求得各个目标函数的最优解,第二部分把求得的解作为遗传算法的初始种群求得多目标问题的Pareto最优解。仿真结果,该算法有较好的有效性、稳定性和订单适应能力。
Ant Colony Algorithm and Generation Algeorithm are two bionic optimization algorithm,they are also two powerful and effective algorithms for solving the production scheduling problems.This paper present a Multiple Ant Colony-Genetic Mixed Algorithm for the Multi-objective Shop scheduling,the first part of this algorithm is to use the Multiple Ant Colony Algorithm to get the optimal solution of every objective function and the next section we use the got solution as the initial population of the Genetic Algorithm to obtain the Pareto optimal solution of the Multi-objective problem.The simulation is used to prove the algorithm＇s validity,stability and order adaptability.
出处
《科技信息》
2012年第11期52-53,共2页
Science & Technology Information
关键词
多目标蚁群算法
遗传算法
多目标车间调度
Multiple ant colony algorithm
Genetic algorithm
Multi-objective shop scheduling
