【作者】 杨薇；

【导师】 罗宜美；

【作者基本信息】 天津大学 ， 工业工程， 2010， 硕士

【摘要】 随着制造业竞争的加剧,越来越多的人都意识到物流在企业发展中所起到的重要作用,设施布置作为物流的一部分也逐渐为人们所关注。合理的设施布置可以有效的降低物流搬运成本、提高产品质量、缩短订货提前期、优化布置环境。本文介绍了多种典型设施布置问题的模型、设施布置方法及其求解算法,分析了它们在求解设施布置问题中的优点和不足。在吸收结合这些模型和方法的基础上,针对它们的不足,提出了含墙体及通道的双目标设施布置方法。首先,在传统设施布置模型和SLP方法的基础上,结合企业的实际布置需要,提出了含墙体及通道的双目标设施布置模型;然后,运用改进后的遗传算法对其进行求解,通过多次迭代得出候选方案,供决策者选择。本文所建立的含墙体及通道的双目标设施布置模型有很强的系统性和实用性。首先,模型所要解决的设施面积不等、设施形状不规则的连续型设施布置问题更加符合现实布置要求,加入墙体及通道后更增加了模型的实用性;其次,模型在传统的设施布置模型的基础上加入非物流相关关系的目标,能够使布置在物料搬运成本和非物流相关性两方面都得到优化;所采用的图论中最短路问题的Dijkstra’s方法求解带通道的设施间距离,比直线距离、矩形距离等计算方式更加能够准确、客观的表示设施间的实际距离,从而保证最终优化结果的准确性。在遗传算法的设计上针对不同的染色体及染色体区段运用不同的遗传操作,确保算法的有效性和全局优化性;采用修正操作解决解码过程中空白区域的问题,提高了设施布置面积的利用率。最后在实证研究部分运用C#语言编写遗传算法程序实现算法的设计和运算,得出优化方案,在结果分析的基础上得出该算法的优越性结论。更多还原

【Abstract】 Nowadays, more and more people have realized the importance of logistics in enterprises in the competitive environment of the manufacturing industry. So does the facility layout problem. Reasonable facility layout can reduce the transportation costs of logistics, improve the quality of products, shorten the lead time, and improve the working environment effectively.This paper describes several classical facility layout problems, and discuses the methods and the algorithms to these problems. By analyzing the advantages and disadvantages of these approaches, this paper proposes a bi-criteria mathematic model for the facility layout problems with inner walls and passages. First, establishes a bi-criteria layout model that has walls and passages based on the traditional facility layout models and SLP method combining the actual needs of enterprises. Then, gives some candidate solutions maked by the improved genetic algorithm for decision-makers to choose.The model this paper proposes has highly systematic and practical use. First, the continuous layout problem of unequal area and irregular shape of facilities is more practical than others, and it is better when adding the factors of inner walls and passages; Second, it is more optimized when concerning material handing costs together with nonmaterial relation requirements; the shortest path and distance between two facilities is calculated using Dijkstra’s algorithm of graph theory, and it is more accurate and objective than traditional methods of straight line or rectangular distance. For the design of the proposed genetic algorithm, different genetic operation is imposed on different chromosomes and segments to ensure the effectiveness and overall optimization of the algorithm; by using the refinement operation in the proposed algorithm, this paper has handled void spaces generated during the decoding process, and improved the utilization of the layout area. Finally, in the part of the empirical study, this paper uses C# language to achieve the genetic algorithm, and draw solutions of the genetic algorithm which can prove the superiority of the algorithm.更多还原