摘要
针对一个生产大型机械产品(如架桥机等)的企业的焊接车间的调度问题进行研究,对m位工人加工n个结构件的随机调度问题建立数学模型,并以最小化最大的加工完成时间的期望与方差为优化目标。为求解该模型,对二进制粒子群算法(BPSO)进行改进,并采用动态领域策略、新的粒子个体极值选择以及一维优化方法求解双目标优化问题。通过实例仿真,结果证实修改后的算法是有效的,并能够找到Pareto前沿解。
The scheduling problem was based on a real welding workshop in a large manufacturing enterprise. A stochastic scheduling problem consisting of m workers and n jobs was dealt with and a mathematic model was developed to minimize maximum expected value and variance of the completion time. In order to solve the problem, Binary Particle Swarm Optimization （BPSO） algorithm was modified, and a dynamic neighborhood strategy, new particle memory updating, and one-dimension optimization method were used to solve two objectives problem. A simulation example was carried out to illustrate that the improved method could efficiently find Pareto front solutions.
出处
《系统仿真学报》
CAS
CSCD
北大核心
2009年第13期3906-3909,3913,共5页
Journal of System Simulation
基金
国家自然科学基金(70871005
70671007)
航空科学基金(2007ZG51075)
