【作者】 张伟；

【导师】 黎冰；

【作者基本信息】 华东理工大学 ， 控制科学与工程， 2014， 硕士

【摘要】 随着我国经济的快速发展,汽车零部件制造业的竞争也比以往任何时候都要激烈,要想能够生存和发展,就要对市场的信息实时的掌握,并能够做出快速的反应,因此复杂的市场环境对这些企业就有了更高的要求。在汽车行业中,零部件企业属于底层环节,在产品质量得到保证的情况下,如果零部件制造企业无法满足客户的需求,对成本的控制不能够应对突发变化,就会失去很多客户,这样企业就会有很大的损失,对公司的发展也是非常不利的。生产计划和生产调度是企业生产管理最重要的部分,好的计划和调度能够充分利用企业的资源,使企业获得最大的效益。本文介绍了汽车零部件行业发展和管理的特点,分析了汽车零部件的生产计划方式,并详细说明了各种生产计划的层次结构。汽车零部件的生产是非常复杂的优化问题,现如今虽然已经提出了许多优化求解方法,但多数只适用于规模较小的问题,而且这些方法各自都存在一定的缺陷。本文将禁忌搜索融入到遗传算法的变异过程中去,用来弥补遗传算法的缺点,从而提出了一种混合算法。本文以汽车零部件生产获得的利润最大化为目标,对汽车零部件生产计划的优化问题进行研究。先根据汽车零部件的生产流程建立了整数规划模型,并在此基础上进行简化,建立了汽车零部件生产计划的随机期望值模型,并通过混合算法进行求解。同时本文还研究了汽车零部件作业车间调度的问题,以最小化完工时间为优化目标,采用遗传算法和禁忌搜索算法相结合的混合算法进行研究。最后本文还通过实验仿真来验证,从得到的结果可以看出,混合算法的设计是可靠和可行的。更多还原

【Abstract】 With the rapid development of economy, the competition in the automotive manufacturing industry is also becoming increasingly fierce. In order to survive and develop, it must have the good ability to respond and adapt complex market environment. Production planning and production scheduling is the core content and key technologies for enterprise production management, whose task is to reach the goal of economic or performance needs.This article based on the actual production situation of automobile parts, to describe the existing workshop production planning and scheduling problems. Automobile parts production is a complex combinatorial optimization problem, which is a typical NP-hard problem. Although it has been proposed many optimization methods for solving the problem, most only apply to smaller issues. Furthermore, these methods have their respective limitations. In this paper, a hybrid algorithm is proposed to solve scheduling problem.In this paper, the profit maximization of automobile parts manufacturing as the goal to research the optimization problems of automobile parts production planning. And establish integer programming model according to auto parts production processes, and on this basis establish a stochastic expected value model. This paper proposes an intelligent algorithm which combines stochastic simulation and hybrid algorithm to solve the problem of production planning for automobile parts. Numerical examples are given out to validate the model and method are reliable. In addition, the article minimize the completion time as the target to research the automobile parts job shop scheduling problem. And use hybrid algorithm which combines genetic algorithm and tabu search algorithm to research the problem, through simulation experiments to verify the reliability and effectiveness.更多还原