数控加工中心任务与刀具集成调度模型及改进自适应遗传算法  

Job and Tool Integrative Scheduling Model in CNC Machining Center and Improved Adaptive Genetic Algorithm

作　　者：周光辉[1,2] 苗发祥 李彦广[1] 

机构地区：[1]西安交通大学机械工程学院,西安710049 [2]西安交通大学机械制造系统工程国家重点实验室,西安710049

出　　处：《西安交通大学学报》2014年第12期1-7,56,共8页Journal of Xi'an Jiaotong University

基　　金：国家自然科学基金资助项目(51175414);教育部新世纪优秀人才支持计划资助项目(NCET-12-0452);国家科技支撑计划资助项目(2012BAH08F02)

摘　　要：为解决数控加工中心任务与刀具的集成优化调度问题,以生产总成本最小为优化目标,建立了考虑任务交货期和工步并行加工的数控加工中心任务与刀具集成调度模型,产生面向数控加工中心任务与刀具的协同优化调度结果。为实现对该调度模型的优化求解,提出了一种改进自适应遗传算法,设计了合理的编码方式和自适应进化操作,并通过任务-刀具关联矩阵保证搜索过程中解的可行性,从而显著提高了算法的收敛性能和求解效率。算例结果表明,该模型能够最大限度地降低加工成本和拖期率,同时算法的收敛速度和稳定性也得到了明显提高,大大降低了问题求解的迭代次数。To solve the integrated scheduling for job and tools in computer numerical control （CNC） machining center, a model considering delivery time and parallel processing of working steps is presented. And the minimized total cost of production is taken as the objective to achieve the collaborative optimization. An improved adaptive genetic algorithm is proposed where a job- tool relationship matrix is adopted to guarantee the legality of solutions, and a rational chromosome encoding and adaptive genetic operations are designed to accelerate the convergence rate and improve solving efficiency. The experimental examples are comparatively analyzed to verify correctness of the model. The proposed algorithm enables to maximally reduce processing cost and job tardiness rate and to improve the convergence rate and stability with greatly reduced iterations.

关 键 词：数控加工中心 刀具调度 并行加工 自适应遗传算法 

分 类 号：TH166[机械工程—机械制造及自动化]