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论文编号：	5537
作者编号：	2120112372
上传时间：	2013/6/10 21:14:22
中文题目：	基于禁忌搜索算法的多产品动态批量问题研究
英文题目：	Research on Multi-product Dynamic Lot Sizing Decision
指导老师：	李勇建
中文关键字：	动态批量问题；禁忌搜索算法；拉格朗日松弛；次梯度算法
英文关键字：	Dynamic Lot Sizing Problem; Tabu search algorithm; Lagrangian relaxation; Subgradient algorithm
中文摘要：	动态批量问题（DLSP，Dynamic Lot Sizing Problem）是一个理论和算法上研究的难点，也是生产实践中的重大经济效益的问题之一。恰当的批量决策，可以避免过量的库存或者频繁的缺货，提高服务质量，降低生产运作成本。 本文以服务性产品为对象，在此背景下研究了多产品动态批量问题（MDLSP，Multi-product Dynamic Lot Sizing Problem）、考虑再制造的多产品动态批量问题（RMDLSP， Multi-product Dynamic Lot Sizing Problem with Remanufactured Constraints）以及考虑使用寿命的多产品动态批量问题（UMDLSP， Multi-product Dynamic Lot Sizing Problem with End-of-use Constraints）。通过对三种不同条件下的多产品动态批量模型的建立与分析，并结合现有的动态批量模型和动态批量算法的国内外研究现状，构造了一种改进次梯度规则下的禁忌搜索算法。该算法首先运用拉格朗日松弛对建立的多产品动态批量模型进行分解，并通过对分解后子模型的分析，设置了各子模型的求解规则，之后本文采用随机的方法产生满足条件的初始解，并通过改进次梯度规则的邻域操作不断的对该初始解进行优化，直到满足终止条件。为了验证该算法的可靠性，本文通过MATLAB程序设计语言对构造的禁忌搜索算法进行编程设计，并引入具体的算例进行仿真求解，通过与动态规划方法、拉尔朗日松弛算法进行比较分析，结果显示：禁忌搜索算法能在较短的时间内获得较好的满意解。并且，本文将考虑再制造的多产品动态批量问题与传统的多产品动态批量问题进行比较，通过总成本的对比，验证了考虑再制造的多产品动态批量总成本低于不考虑再制造的多产品动态批量总成本。 本文的主要创新点是：研究了服务性产品的多产品动态批量问题，并构造了一个能有效解决不同条件下多产品动态批量问题的禁忌搜索算法，为企业的动态批量问题提供了一个科学的、合理的解决方案。并且本文对比分析了相同市场需求下再制造企业与传统企业的多产品动态批量决策。验证了在产品种类、市场需求等外界因素相同的前提下，服务性产品的回收再制造能降低生产成本，提高企业利润，从而为传统企业进行回收再制造的决策提供了较好的指导意见。
英文摘要：	Dynamic Lot Sizing Problem is a difficult research of a theory and algorithm，and also one of the great economic benefit in the practice of production. Appropriate Lot Sizing decision-making can avoid excessive inventory or frequent shortage, improve service quality, and reduce the cost of production operation. This paper studies the dynamic lot sizing problem with multiple products，Multi-product Dynamic Lot Sizing Problem with Remanufactured Constraints，Multi-product Dynamic Lot Sizing Problem with End-of-use Constraints Based on the service product as the object. Through the establishment and analysis of the three kinds of multi-product dynamic lot-sizing model under different conditions, and combine with the current research situation of the dynamic Lot Sizing model and the dynamic Lot Sizing model algorithm at home and abroad, presents an tabu search algorithm under the rules of improved subgradient. The algorithm first uses Lagrange relaxation to decompose dynamic lot-sizing model of product is established, and through the analysis of the decomposed sub-model, set up solving rules of the sub-model ,then this paper adopts the random method to generate initial solution, and through improved subgradient rule neighborhood operation continuously on the initial solution optimization until satisfied termination condition. In order to verify the reliability of the algorithm, This paper applied the MATLAB programming language to the tabu search algorithm for programming, and introduces the concrete examples of simulation, compare with the dynamic programming method, the Lagrangian relaxation algorithm, the results showed: tabu search algorithm can obtain satisfactory solution in a short time. And, this paper compare Multi-product Dynamic Lot Sizing Problem with Remanufactured Constraints with traditional Multi-product Dynamic Lot Sizing Problem, verified the Multi-product Dynamic Lot Sizing Problem with Remanufactured Constraints is lower than Multi-product Dynamic Lot Sizing Problem by comparing the total cost. The main innovation of this thesis is: Research on Multi-product Dynamic Lot Sizing Problem of the service product, and constructs a tabu search algorithm which can provides a scientific and reasonable solution for the enterprise. And the paper compare the same remanufacturing enterprises with traditional enterprises under the same market demand show that the s recycling of service product can reduce the production cost, improve corporate profits, and provides a good guidance for traditional enterprises.
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