摘要
针对车间调度问题(Job Shop Problem,JSP)的特点,提出一种改进遗传算法。该方法利用剩余作业时间最多(MostWork Remaining,MWR)的工件优先排列的启发式规则来产生初始种群,并且在进化过程中采用分代交叉算子进行操作来避免算法早熟。通过分析算例结果表明,该改进遗传算法可以在进化初期就得到比较理想的调度方案,而且优化收敛速度快、结果优,更适用于解决车间调度问题。
Proposes an improved Genetic Algorithm(GA)based on the characteristics of the Job Shop Problem(JSP),which generates the initial population with the MWR rule and avoids the premature with the different sub-generation crossover operations in the evolution process.A case study shows that the genetic algorithm can produce more powerful scheduling results in the early evolution stages and is able to solve the Job Shop Problem(JSP)effectively with more good results and fast convergence.
出处
《现代制造工程》
CSCD
北大核心
2010年第10期35-37,51,共4页
Modern Manufacturing Engineering
关键词
车间调度问题
遗传算法
启发式
Job Shop Problem(JSP)
Genetic Algorithm(GA)
heuristic