基于混合粒子群算法具有交货期瓶颈的作业车间调度问题  

Job Shop Scheduling for Due-time Bottleneck Based on HPSO Algorithm

作　　者：鲁建厦[1] 邓伟[1] 董巧英[1] 

机构地区：[1]浙江工业大学,杭州310014

出　　处：《中国机械工程》2014年第5期624-629,共6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(LY12E05021);浙江省教育厅科研项目(Y201121984);浙江工业大学校级自然科学研究基金资助项目(2013XZ005)

摘　　要：为了解决一类具有交货期瓶颈的作业车间调度问题,给出了基于订单优势的交货期满意度和交货期瓶颈资源确定方法,以工件拖期加权和最小为优化目标,建立了基于交货期满意度和瓶颈资源约束的作业车间调度模型;为了求解该调度模型,设计了一种基于模拟退火的混合粒子群算法,该算法采用随机工序表达方式进行编码,并在模拟退火算法中引入变温度参数来提高算法效率。通过随机仿真,分别采用PSO-SA、SA和PSO对所建立的调度模型进行求解,结果显示PSO-SA算法的广泛性好、求解效率高且算法的稳定性好,验证了模型和算法的有效性。To solve a kind of job shop scheduling problem for due--time bottleneck, taking the tardiness weighted sum as the optimization objective, a model based on due--time degree of satisfaction and bottleneck resources was presented. According to the characteristics of job shop, a hybrid algorithm with particle swarm optimization and simulated annealing algorithm was proposed to solve the model. In the hybrid algorithm, a random process expression method for encoding was taken. And a dynamic temperature parameter was introduced to the simulated annealing algorithm to increase the algorithm＇s efficiency. The simulation was given to test the model and algorithms presented here- in. And the testing results prove the method is effective.

关 键 词：作业车间 交货期瓶颈资源 交货期满意度 混合粒子群算法 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]