节点文献
一种求解车间作业调度问题的改进遗传算法
Improved Genetic Algorithm for Solving Job-Shop Scheduling Problem
【摘要】 变批量和个性化产品的现代生产方式,使得调度问题在当今生产中日渐受到重视,为克服传统遗传算法在求解车间作业调度问题时的早熟收敛,结合基于工序编码和位置列表编码的优势,设计了混合编码方式,并将局部搜索运用到变异算子中,通过实例验证了该算法的有效性。
【Abstract】 As the scalable batch and individual character product are needed in modern manufacturing mode,Job-Shop scheduling problem is attached with great importance.To avoid premature convergence,which appeared in the course of solving Job-Shop scheduling by applying conventional GA,an improved combined code method was proposed by taking advantages of operation-based representation encode and operation-based location list encode,and local search was applied in mutation operator.Its efficiency was validated by applying improved GA to examples.
【关键词】 车间作业调度;
混合编码;
变异算子;
局部搜索;
【Key words】 Job-Shop scheduling; Combined code; Mutation operator; Local search;
【Key words】 Job-Shop scheduling; Combined code; Mutation operator; Local search;
【基金】 教育部高等学校博士学科点专项科研基金(20040422023);山东省优秀中青年科学家科研奖励基金(2005BS05001)
- 【文献出处】 机床与液压 ,Machine Tool & Hydraulics , 编辑部邮箱 ,2007年01期
- 【分类号】TP18
- 【被引频次】1
- 【下载频次】272