在经济全球化的影响下,半导体测试行业中传统的依靠人力手动处理Excel统计数据的排产方式已经落伍,现今主要采用信息化管理模式,用ERP、MES、APS等设备管理软件优化企业管理机制,提高市场竞争力。针对半导体企业的需求,在分析半导体测...在经济全球化的影响下,半导体测试行业中传统的依靠人力手动处理Excel统计数据的排产方式已经落伍,现今主要采用信息化管理模式,用ERP、MES、APS等设备管理软件优化企业管理机制,提高市场竞争力。针对半导体企业的需求,在分析半导体测试行业主要业务流程的基础上,研究面向半导体测试企业的高级计划与排程系统(Advanced Planning and Scheduling,APS)的开发与实现,妥善管理和规划企业资源,帮助企业高效快速地制定合理的生产排程计划,从而提高企业效率,增强市场竞争力。实践证明,设计的APS系统稳定可靠,达到了预期目标。展开更多
No-wait flowshop scheduling problems with the objective to minimize the total flow time is an important se-quencing problem in the field of developing production plans and has a wide engineering background. Genetic al...No-wait flowshop scheduling problems with the objective to minimize the total flow time is an important se-quencing problem in the field of developing production plans and has a wide engineering background. Genetic algo-rithm (GA) has the capability of global convergence and has been proven effective to solve NP-hard combinatorial op-timization problems,while simple heuristics have the advantage of fast local convergence and can be easily imple-mented. In order to avoid the defect of slow convergence or premature,a heuristic genetic algorithm is proposed by in-corporating the simple heuristics and local search into the traditional genetic algorithm. In this hybridized algorithm,the structural information of no-wait flowshops and high-effective heuristics are incorporated to design a new method for generating initial generation and a new crossover operator. The computational results show the developed heuristic ge-netic algorithm is efficient and the quality of its solution has advantage over the best known algorithm. It is suitable for solving the large scale practical problems and lays a foundation for the application of meta-heuristic algorithms in in-dustrial production.展开更多
文摘在经济全球化的影响下,半导体测试行业中传统的依靠人力手动处理Excel统计数据的排产方式已经落伍,现今主要采用信息化管理模式,用ERP、MES、APS等设备管理软件优化企业管理机制,提高市场竞争力。针对半导体企业的需求,在分析半导体测试行业主要业务流程的基础上,研究面向半导体测试企业的高级计划与排程系统(Advanced Planning and Scheduling,APS)的开发与实现,妥善管理和规划企业资源,帮助企业高效快速地制定合理的生产排程计划,从而提高企业效率,增强市场竞争力。实践证明,设计的APS系统稳定可靠,达到了预期目标。
基金Project 60304016 supported by the National Natural Science Foundation of China
文摘No-wait flowshop scheduling problems with the objective to minimize the total flow time is an important se-quencing problem in the field of developing production plans and has a wide engineering background. Genetic algo-rithm (GA) has the capability of global convergence and has been proven effective to solve NP-hard combinatorial op-timization problems,while simple heuristics have the advantage of fast local convergence and can be easily imple-mented. In order to avoid the defect of slow convergence or premature,a heuristic genetic algorithm is proposed by in-corporating the simple heuristics and local search into the traditional genetic algorithm. In this hybridized algorithm,the structural information of no-wait flowshops and high-effective heuristics are incorporated to design a new method for generating initial generation and a new crossover operator. The computational results show the developed heuristic ge-netic algorithm is efficient and the quality of its solution has advantage over the best known algorithm. It is suitable for solving the large scale practical problems and lays a foundation for the application of meta-heuristic algorithms in in-dustrial production.
