摘要
为解决混合流水车间分批调度问题,提出一种三级递阶结构的蚁群算法。算法中,第一级蚁群算法设计了一种批量大小动态结合的柔性分批策略,完成产品的批次划分;第二级蚁群算法考虑工件在各设备的加工时间和设备可用能力,设计蚂蚁设备间的转移概率,完成工序约束下各批次的设备选择;第三级蚁群算法考虑同一设备上批次顺序相关的换批时间,设计蚂蚁批次间的转移概率,完成各设备的批次排序。通过实例仿真,分别对分批算法和混合流水车间调度算法性能进行比较分析和评价,结果表明了算法的有效性和优越性。最后从生产实际出发给出算例,验证了算法的有效性和对生产实践的指导作用。
To solve the problem of hybrid flow shop batch scheduling,a novel Ant Colony Optimization（ACO）algorithm with three level hierarchical structures was proposed.A flexible batching strategy was put forward in the first level of ACO to complete the batch partition of products.By considering the process time and available capacity of equipment in second level of ACO,the transition probability between ant equipments was designed,and the equipment selection of each batch under process constraint was fulfilled.Through considering the relevant batch time of batch sequence on same equipment,the transfer probabilities of ants between machines were designed in third level of ACO,and batch scheduling of equipment was completed.Performance of batch algorithm and hybrid flow shop scheduling algorithm were evaluated respectively through simulation experiment,and the results demonstrated the feasibility and effectiveness of proposed algorithm.An example from the practical production was addressed to express the guidance for production practice.
出处
《计算机集成制造系统》
EI
CSCD
北大核心
2013年第7期1640-1647,共8页
Computer Integrated Manufacturing Systems
基金
国家863计划资助项目(2012AA040907)
苏州市科技计划资助项目(SG201131)~~
关键词
蚁群算法
混合流水车间
分批调度
仿真
ant colony algorithm
hybrid flow shop
batch scheduling
simulation
