遗传算法在多品种小批量模式MPS中的应用  

Applications of Genetic Algorithm in production planning of multi-categories and small batch mode

作　　者：杨美荣[1] 崔曼曼[2] 史建锋[2] 肖玲诺[3] 

机构地区：[1]哈尔滨工业大学经济管理学院(威海),山东威海264209 [2]哈尔滨工业大学管理学院,哈尔滨150001 [3]哈尔滨工业大学人文与社会科学学院,哈尔滨150001

出　　处：《计算机工程与应用》2013年第13期266-270,共5页Computer Engineering and Applications

基　　金：山东省自然科学基金(No.2009ZRA10043)

摘　　要：结合准时制生产和约束理论,以"关键设备产能"和"产品提前期"两大约束为重心,确定以关键工作中心利用率最高和提前/拖期罚款最少作为MPS模型的两个目标,提出了一种多品种、小批量生产模式下企业MPS的双目标排单模型的建立思路和方法;应用遗传算法对模型进行优化计算,通过对企业实例数据的运行结果分析,验证了方案的有效性。According to Just-in-Time production and Theory of Constraints, centering on two restrictions of producing ability of key work center and production lead time, determining the maximum utilization of key work center and the least earliness/tardiness fine as the two goals of MPS model, this paper presents a double-goal MPS model based on multi-variety and small-batch enterprise. It uses GA to optimize the MPS model. Through analyzing the results of the enterprise data, GA has been proved to be effective.

关 键 词：主生产计划 约束理论 准时制生产 遗传算法 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]