基于维信息共享的粒子群优化算法在作业车间调度中的应用  

Application of Dimensional Information Sharing-Based Particle Swarm Optimization Algorithm for Production Scheduling

作　　者：温海骏[1,2] 侯世旺[2] 

机构地区：[1]合肥工业大学机械与汽车工程学院,安徽合肥230009 [2]中北大学机械与动力工程学院,山西太原030051

出　　处：《工业工程》2014年第1期30-36,共7页Industrial Engineering Journal

基　　金：国家重点基础研究发展计划资助项目(973计划,2011CB013406);教育部人文社会科学青年基金资助项目(12YJC630111)

摘　　要：为提高车间调度算法的寻优性能,提出了一种基于维信息共享的粒子群算法的车间调度问题解决方案。该算法对粒子群的认知过程和更新过程进行了研究,通过维信息共享和动态认知概念的引入,实现了优化问题维信息的沟通和交流,通过增加扰动因子克服算法的过早收敛,提高了对优化问题的适应能力。通过对3个连续函数优化问题的测试,得到了最佳的平均值和标准差,并对14个JSP标准测试案例进行仿真。结果表明无论是在求解质量还是收敛速度方面都优于其他几种算法,说明该算法能够有效地、高质量地解决作业车间调度问题。In order to improve the performance of shop scheduling algorithm , a dimensional information sharing-based particle swarm optimization ( PSO) algorithm for workshop scheduling problem is proposed . The cognitive process and update process of particle swarm are studied .By introducing the concept of di-mensional information sharing and dynamically cognizing , dimensional information of optimization problem can be communicated and exchanged .The power of adapting to optimization problem of PSO is increased through adding disturbance factor to overcome premature convergence of the algorithm .Finally, the best mean value and the standard deviation are obtained through test of three continuous function optimization problems.The simulation results of fourteen standard test cases for JSP show that the algorithm is better than several other algorithms both in terms of solution quality and convergence speed .The results illustrate that the algorithm can solve the workshop scheduling problem with high efficiency and quality .

关 键 词：作业车间调度 粒子群优化算法 维信息共享 

分 类 号：TP278[自动化与计算机技术—检测技术与自动化装置]