基于改进蝙蝠算法的物流中心选址问题研究

发布时间：2018-04-10 09:18

本文选题：物流中心　切入点：选址模型　出处：《河南大学》2017年硕士论文

【摘要】：随着经济的发展和经济体制改革的深入,物流业在我国发展迅速且前景看好。从宏观上来讲,物流对一个国家经济的发展起着至关重要的作用,从微观上来讲,物流对提高一个企业竞争力来说意义重大。物流中心作为物流系统中的重要节点,其选址在整个物流系统中显得十分重要,选址的成功与否决定了整个物流系统的形状、结构和模式,不仅会影响到物流中心自身的运营成本和绩效以及未来发展,还会影响到整个物流系统是否能够高效运营。因此,对物流中心选址问题开展研究十分有意义。现实中,物流中心选址往往是动态的、多目标约束的、高度非线性的,由其转化而来的问题往往都是高度非线性的复杂问题,其计算复杂度往往呈指数增长,传统计算方法已经很难对这类问题求解。借助于计算机,智能优化算法成为目前解决该类问题的有效方法之一。于2010年提出的蝙蝠算法(Bat-inspired Algorithm),以其模型简单、易于实现、收敛速度快、寻优能力强等特点,被广泛应用解决高度非线性优化问题和现实世界的各种工程问题。本文将蝙蝠算法进行有效改进,然后用于求解物流中心选址问题。本文的主要研究内容包括以下几个方面:(1)概述物流中心的相关概念、物流中心选址的基本理论和方法模型。(2)介绍基本蝙蝠算法,在分析惯性权重的基础上,选取指数递减的惯性权重引入到蝙蝠算法对其进行改进,提出具有指数递减惯性权重的蝙蝠算法,以提高其计算精度、减少其运行时间,并通过7个标准测试函数进行仿真实验,证明改进蝙蝠算法可行性和有效性。(3)将改进的蝙蝠算法应用到物流中心选址问题上,对物流中心选址问题构建算法编程,用改进的蝙蝠算法求解,通过与基本蝙蝠算法的求解结果对比,与Lingo软件的求解结果对比,表明改进蝙蝠算法求解物流中心选址问题的有效性以及先进性。本文为蝙蝠算法的改进研究提供新的思路,为智能优化算法求解物流中心选址问题提供新的参考,具有一定的理论意义和现实意义。
[Abstract]:With the development of economy and the deepening of economic system reform, the logistics industry is developing rapidly and has a bright future in China.From a macro point of view, logistics plays a vital role in the development of a country's economy, and from a micro point of view, logistics plays a significant role in improving the competitiveness of an enterprise.As an important node in the logistics system, the location of the logistics center is very important in the whole logistics system. The success of the location selection determines the shape, structure and mode of the whole logistics system.It will not only affect the operation cost and performance of logistics center and its future development, but also affect whether the whole logistics system can operate efficiently.Therefore, it is very meaningful to study the location of logistics center.In reality, logistics center location is often dynamic, multi-objective constrained, highly nonlinear, and the problems transformed from it are often highly nonlinear complex problems, and their computational complexity often increases exponentially.The traditional calculation method has been difficult to solve this kind of problem.With the help of computer, intelligent optimization algorithm has become one of the effective methods to solve this kind of problem.Bat-inspired algorithm, proposed in 2010, is widely used to solve highly nonlinear optimization problems and various engineering problems in the real world because of its simple model, easy implementation, fast convergence speed and strong optimization ability.In this paper, the bat algorithm is improved effectively, and then used to solve the logistics center location problem.The main research contents of this paper include the following several aspects: 1) summarizing the related concepts of logistics center, the basic theory and method model of logistics center location, introducing the basic bat algorithm, and analyzing the inertial weight.The inertial weight of exponential decline is introduced into the bat algorithm to improve it, and the bat algorithm with exponential decreasing inertia weight is proposed to improve its calculation accuracy and reduce its running time.The simulation results of seven standard test functions show that the improved bat algorithm is feasible and effective. The improved bat algorithm is applied to the logistics center location problem, and the algorithm for constructing the logistics center location problem is programmed.The improved bat algorithm is compared with the basic bat algorithm and the Lingo software. It shows that the improved bat algorithm is effective and advanced in solving the logistics center location problem.This paper provides a new way of thinking for the improvement of bat algorithm and a new reference for intelligent optimization algorithm to solve the problem of logistics center location. It has certain theoretical and practical significance.
【学位授予单位】：河南大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F252;TP18

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