基于改进免疫遗传算法的混合车间调度研究  

Improved Immune Genetic Algorithm for Mixed-model Scheduling Problem

作　　者：汤洪涛[1] 丁彬楚[1] 李修琳[2] 鲁建厦[1] 

机构地区：[1]浙江工业大学,杭州310032 [2]浙江工商大学,杭州310018

出　　处：《中国机械工程》2014年第9期1189-1194,1201,共7页China Mechanical Engineering

基　　金：国家自然科学基金资助项目(70971118);浙江省自然科学基金资助项目(Y1111118;LY12E05021);浙江省科技厅重大科技专项与优先主题项目(2009C11164)

摘　　要：建立了以最大总完成时间最小为目标的混合车间调度模型。该模型包括作业车间和并行流水装配车间两部分调度问题。为降低问题求解难度,采用分解的策略对调度问题分阶段求解,并引入多Agent协商机制和模拟退火算法与免疫遗传算法相结合,提出了基于分解策略的免疫遗传算法,并通过在某汽车减振器企业的实施验证了模型和算法的有效性。A hybrid workshop scheduling mixed-model with the purpose of minimum makespan was proposed.Job shop scheduling problem and parallel assembly flow shop scheduling problem were both included in this model.To reduce the solving difficulty,an improved immune genetic algorithm mixed with the decomposition strategy was put forward.In this algorithm,the multi-agent negotia-tion mechanism and the simulated annealing algorithm were introduced.In the end,the validities of the model and algorithm were proved by the implement in an automobile shock absorber enterprise.

关 键 词：柔性作业车间 并行流水装配车间 分解策略 免疫遗传算法 

分 类 号：TH166[机械工程—机械制造及自动化]