摘要
构造了求解极小化总完工时间的置换调度问题的改进混合遗传算法:先采用构造型启发式算法和随机方法共同产生初始种群,然后在选择、交叉和变异等遗传操作之前借助禁忌搜索算法寻找每个个体的局部最优解组成当前种群,再应用种群整体替换策略保存种群中的优秀个体构成新一代种群。改进混合遗传算法有机地结合了禁忌搜索算法的局部搜索性能和遗传算法的全局搜索性能。仿真实验表明,改进混合遗传算法具有比构造型启发式算法和禁忌搜索算法更好的鲁棒性和寻优性能。
An improved hybrid genetic algorithm （IHGA） was proposed for permutation flowshop scheduling to minimize total flowtime. Firstly, initial solutions were generated by constructive heuristic and random method. Then tabu search was used to achieve local solutions of initial population before genetic operation was taken. Lastly, a population management strategy was designed to generate new population. This method combined the local searching property of tabu search with the global searching property of genetic algorithm. Computational experiments indicate that the proposed IHGA outperforms the constructive heuristic algorithm and tabu search in both robustness and goodness of searching.
出处
《中国机械工程》
EI
CAS
CSCD
北大核心
2006年第16期1707-1710,共4页
China Mechanical Engineering
基金
国家自然科学基金资助项目(70271033
60574070)
关键词
遗传算法
启发式算法
禁忌搜索
调度
genetic algorithm
heuristic algorithm
tabu search
scheduling
