摘要
针对批量与排序的集成问题设计一种遗传算法和禁忌搜索相结合的混合算法,用遗传算法作为主框架优化批量,排序部分由禁忌搜索单独优化,并将排序最优解反馈到遗传算法的主框架中生成集成计划继续寻优。遗传算法的选择算子和变异算子分别采用不同的自适应机制,以提高算法的搜索能力和收敛速度。对3种不同规模算例进行测试,其结果与其他算法比较,验证了所提算法的有效性。
A hybrid approach combining genetic algorithm（GA） and tabu search is designed to solve the joint lot sizing and scheduling problem,where GA is applied as a main frame to optimize lot sizing and the scheduling is optimized by tabu search alone,and the optimal solution of scheduling is returned to the main frame to generate integrated plans for continued searching.Different self-adaptive mechanisms are respectively used in selection operator and mutation operator to improve the search capability and convergence the speed of GA.Experiments are conducted on three kinds of different-scaled problems.Compared with other algorithms,the obtained results validate the effectiveness of the proposed method.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2012年第4期833-838,共6页
Systems Engineering and Electronics
基金
国家自然科学基金(71071008)
郑州市科技计划项目(10PTGG343-7)资助课题
关键词
批量与排序集成问题
遗传算法
禁忌搜索
自适应机制
joint lot sizing and scheduling problem（JLSP）
genetic algorithm（GA）
tabu search（TS）
self-adaptive mechanism
