有限缓冲区流水车间调度的混合人工蜂群算法  

Hybrid artificial bee colony algorithms for flowshop scheduling problem with limited buffers

作　　者：张培文[1] 潘全科[1] 李俊青[1] 段俊华[1] 

机构地区：[1]聊城大学计算机学院,山东聊城252059

出　　处：《计算机集成制造系统》2013年第10期2510-2520,共11页Computer Integrated Manufacturing Systems

基　　金：国家自然科学基金资助项目(61174187;61104179);教育部高等学校基本科研业务费资助项目(N110208001);东北大学科研启动基金资助项目(29321006);辽宁省自然科学基金资助项目(2013020016);山东省智能信息处理与网络实验室资助项目~~

摘　　要：针对以最大完工时间为目标的有限缓冲区流水车间调度问题,提出有效的混合人工蜂群算法。采用WPFE启发式算法进行种群的初始化,以提高初始种群的质量。将遗传算法应用到离散人工蜂群算法的引领蜂阶段,设计了基于嵌入结构、串行结构、协同结构、并行结构、概率选择结构和双种群结构的六种混合调度算法。基于插入和交换邻域的邻域搜索算法进一步增强了混合算法的局部开挖能力。通过仿真实验证明了所提算法的高效性和优越性。Aiming at the limited buffer flow shop scheduling problem with maximum makespan as objective, an effec- tive Hybrid Artificial Bee Colony （HAP, C） algorithm was proposed. The population was initialized by WPFE heu- ristic algorithm to improve the quality of initial population. The genetic algorithm was introduced into the employed bee stage of artificial bee colony to design six hybrid scheduling algorithms based on embedded structure, collabora- tive structure, serial structure, concurrent structure, probability selection structure and bi-group structure. To en- hance the algorithm＇s exploitation ability, an effective local search method based on insert and swap neighborhood was embedded in HABC. The computation results demonstrated the effectiveness and superiority of the proposed HABC.

关 键 词：有限缓冲区 流水车间调度问题 人工蜂群算法 遗传算法 混合算法 邻域搜索算法 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]