油库选址决策的二层优化模型研究

油库物流设施的选址决策属于战略管理层的决策,它是整个物流系统运作的基础.油库的选址决策是库存和运输决策的基础,库存决策和运输决策则是在整个油品配送系统规划框架内对油库选址决策的完善和延伸.如何进行科学的油库选址是企业所关心的问题.本文将在考虑影响选址的定性成本因素以及运营过程中的非成本因素、定性和定量相结合的基础上利用多层决策理论,将油库选址问题归结为一个二层优化模型,并提出了确定理想选址区域和可行点的相关方法的计算方法.数值实验表明该算法是可行的.本文的结论对实际决策问题具有一定的借鉴作用.     

考虑需求不确定的多级应急物流设施选址研究

为了对急物流设施选址问题进行合理的研究,建立了包含配送中心、配送点和需求点的多级应急物流网络。基于应急物资需求特点,使用三角模糊数表示应急物资需求的不确定性,同时考虑应急救援成本和应急救援时间两个目标,建立了应急物流设施选址模型。采用去模糊化方法将三角模糊数转化为确定数,利用成本和时间的单目标的最优结果将多目标转化为相对值,再对时间和成本目标进行加权处理,既消除了不同目标之间的单位及数量级差异,还可以进行动态调整。设计了遗传算法对模型进行求解,通过实际算例表明了模型和算法可以有效地解决应急物流设施选址问题。     

考虑设施中断情景的震后救援初期应急物流网络优化设计

在震后救援初期,构建合理的应急物流网络,对于快速有效供应应急物资、减轻灾情具有重大价值。在传统可靠性选址问题与应急设施选址-分配问题的基础上,考虑震后救援初期的阶段性特征、设施中断情景、多品种模糊需求、设施能力限制等因素,建立了一个适用于震后救援初期的应急设施选址-分配模型。通过三角模糊数的期望值公式将模糊需求去模糊化。在此基础上,考虑模型特点,设计了一种整数编码的混合遗传算法。最后,以5·12汶川地震为背景,构造算例进行数值仿真。验证了所提模型和算法。结果表明:考虑设施中断情景后,即使系统中的部分设施失效,整个网络仍能较好运行,且优化结果更具可靠性和稳健性。     

连续设施选址:模型、方法与应用

给定度量空间和该空间中的若干顾客,设施选址为在该度量空间中确定新设施的位置使得某种目标达到最优。连续设施选址是设施选址中的一类重要问题,其中的设施可在度量空间的某连续区域上进行选址。本文对连续设施选址的模型、算法和应用方面的工作进行了综述。文章首先讨论了连续设施选址中几个重要元素,包括新设施个数、距离度量函数、目标函数;然后介绍了连续选址中的几种经典模型和拓展模型;接着概述了求解连续选址问题的常用优化方法和技术,包括共轭对偶、全局优化、不确定优化、变分不等式方法、维诺图;最后介绍了连续设施选址的重要应用并给出了研究展望。     

化工园区应急设施区间规划选址模型研究

应急设施选址受应急物资需求量的影响。为优化应急设施选址布局,提高突发事件应急处置能力,以化工园区突发事件为研究背景,对化工园区突发事故下应急设施选址进行研究。考虑到化工园区突发事件的随机性和复杂性、突发事件应急物资需求的不确定性等特点,以应急设施选址安全性最大、经济性和服务效益最好为目标,基于传统确定性应急设施选址模型,构建了不确定需求条件下化工园区应急设施选址区间规划数学模型。模型中应急物资需求量是一个区间值,通过引入区间规划理论和模糊理论对模型进行求解,不仅避免了不确定参数随机概率分布的波动率,而且也降低了模型求解过程中的不确定性。最后,以园区各企业潜在事故为工程背景进行实例分析,得到园区应急设施的布局方案。结果表明,模型的求解效果较好,可为园区应急设施选址决策提供参考依据。     

基于第三方回收的废旧家电逆向物流网络设计

针对第三方参与废旧家电回收问题进行研究,以第三方家电回收企业利润最大化和回收中心对居民产生的负效用最小化为目标,考虑废旧家电在回收数量、回收质量以及客户需求量等方面的不确定性,建立多周期多目标的废旧家电逆向物流网络模型.采用改进加权平均求解法将双目标规划转化为单目标规划后,再采用区间规划方法对模型进行确定性转化.模型数值仿真得到的优化解能为企业在物流设施选址以及不同周期下的市场缺货量、设施间流量分配等提供一个灵活的决策方案.     

高校物流公司联盟服务站选址的研究

以国内高校周边物流公司的现状入手,论述高校设立物流公司联盟服务站的特点和优势,提出高校物流公司联盟服务站设计程序.基于离散选址模型及其对高校物流联盟服务站选址模型的启示,给出高校物流公司联盟服务站选址的计算模型.最后,以某高校为例进行物流公司联盟服务站选址规划并与该校物流联盟服务站实际地址作比较,比较结果表明,选址计算法是一个有效的算法,可以很好地应用在高校物流公司联盟服务站选址的研究中.     

"物流配送中心选址的随机数学模型"的有效性研究

从实际应用出发，对文献[1]中提出物流配送中心选址的随机数学模型进行了有效性分析。通过计算机模拟得到的数据，分别应用随机数学模型和传统选址方法对不同规模的配送网络进行选址，通过分析两者在不同条件下的总费用，得到了该随机模型的一些有趣的性质，为实际中的应用提供了依据。     

有容量限制的可靠性固定费用选址问题

设施网络可能面临各种失灵风险,而设施选址属于战略决策问题,短期内难以改变,因而在选址设计时需要充分考虑设施的非完全可靠性。本文针对无容量限制的可靠性固定费用选址问题进行扩展,进一步考虑设施的容量约束,基于非线性混合整数规划方法建立了一个有容量限制的可靠性固定费用选址问题优化模型。针对该模型的特点,应用线性化技术进行模型转化,并设计了一种拉格朗日松弛算法予以求解。通过多组算例分析,验证了算法的性能。算例分析结果表明设施失灵风险和设施容量对于选址决策有显著影响,因而在实际的选址决策过程中有必要充分考虑设施的失灵风险及容量约束。     

基于遗传算法的木材物流中心选址研究

分析了木材物流模式,建立物流中心选址的数学模型,研究遗传算法求解选址模型的方法,并以永安林业集团股份有限公司的木材物流数据为基础,提出研究区域内木材物流中心选址的实际模型,采用可重复自然数编码的遗传算法求解模型,运用VB编写相应的程序,提高选址决策的效率和精度。     

电子商务环境下考虑退货的选址库存问题模型与算法

选址库存问题(location inventory problem, LIP)是物流系统集成的经典问题之一,也是企业需要面对的管理决策难题。本文考虑在电子商务环境下无质量缺陷的退货商品可简单再包装后重新进入销售市场这一现实情况,对设施选址和库存控制进行集成优化,构建随机需求下有退货的LIP模型。针对此问题求解的复杂性,设计了改进的自适应混合差分进化算法对模型进行整体求解。最后,通过多组算例验证了模型和算法的实用性和优越性,可为设施选址、库存控制和商品配送回收决策提供重要参考依据。     

Condorcet Winners for Public Goods

In this work, we consider a public facility allocation problem decided through a voting process under the majority rule. A location of the public facility is a majority rule winner if there is no other location in the network where more than half of the voters would have been closer to than the majority rule winner. We develop fast algorithms for interesting cases with nice combinatorial structures. We show that the computing problem and the decision problem in the general case, where the number of public facilities is more than one and is considered part of the input size, are all NP-hard. Finally, we discuss majority rule decision making for related models.     

井位不确定环境下的油田仓库选址问题

油田工作中,合理的仓库选址决策不仅能节约物流成本,而且能提高油田作业效率。现有研究通常基于当前的油井位置(简称井位),没有考虑未来井位变化对仓库选址的影响。同时井位受到地下储层条件及油气公司远景规划等因素影响,未来的井位具有很强的不确定性。此外,仓库选址决策属中长期决策,将长期影响油田的物流费用、管理工作甚至开发工作,而且油田生产要求仓库能持续供应物资,所以油田仓库选址应考虑井位的不确定性和仓库服务中断等因素。本文首先根据油田井位分布和钻井规划采用随机模拟方法模拟未来井位,建立并求解考虑设施中断的离散选址模型。然后以鄂南油区物资仓库选址问题为例,模拟井位并求解仓库选址问题,从8个候选点中选出3个建库/租库。最后,分析井位和需求量变化对仓库选址结果的影响。井位不确定环境下油田物资仓库选址问题的研究,不仅对油田物流系统管理的研究具有一定的理论意义,也对油田的物流决策有重要的现实意义。     

Location of retail facilities under conditions of uncertainty

Models for the optimal location of retail facilities are typically premised on current market conditions. In this paper we incorporate future market conditions into the model for the location of a retail facility. Future market conditions are analyzed as a set of possible scenarios. We analyze the problem of finding the best location for a new retail facility such that the market share captured at that location is as close to the maximum as possible regardless of the future scenario. The objective is the minimax regret which is widely used in decision analysis. To illustrate the models an example problem is analyzed and solved in detail.     

Dynamic facility location when the total number of facilities is uncertain: A decision analysis approach

Models developed to analyze facility location decisions have typically optimized one or more objectives, subject to physical, structural, and policy constraints, in a static or deterministic setting. Because of the large capital outlays that are involved, however, facility location decisions are frequently long-term in nature. Consequently, there may be considerable uncertainty regarding the way in which relevant parameters in the location decision will change over time. In this paper, we propose two approaches for analyzing these types of dynamic location problems, focussing on situations where the total number of facilities to be located in uncertain. We term this type of location problem NOFUN (Number Of Facilities Uncertain). We analyze the NOFUN problem using two well-established decision criteria: the minimization of expected opportunity loss (EOL), and the minimization of maximum regret. In general, these criteria assume that there are a finite number of decision options and a finite number of possible states of nature. The minisum EOL criterion assumes that one can assign probabilities for the occurrence of the various states of nature and, therefore, find the initial set of facility locations that minimize the sum of expected losses across all future states. The minimax regret criteria finds the pattern of initial facility locations whose maximum loss is minimized over all possible future states.     

Competitive facility location and design with reactions of competitors already in the market

A new retail facility is to locate and its service quality is to determine where similar facilities of competitors offering the same goods are already present. The market share captured by each facility depends on its distance to customers and its quality, which is described by a probabilistic Huff-like model. In order to maximize the profit of the new facility, a two-stage method is developed, which takes into account the reactions of the competitors. In the quality decision stage, the competitive decision process occurring among facilities is modelled as a game, whose solution is given by its Nash equilibrium. The solution, which can be represented as functions of the location of the new facility, is obtained by analytical resolution of a system of equations in the case of one facility in the market or by polynomial approximation in the case of multiple facilities. In the location decision stage, an interval based global optimization method is used to determine the best location of the new facility. Numerical experiments on randomly generated instances demonstrate the effectiveness of the method.     

A new method for managing the uncertainties in evaluating multi-person multi-criteria location choices,using a perceptual computer

The international logistics centers choice problem is a very important issue in International logistics. The location choice problem usually involves numbers and words in which all of the criteria are weighted using words and the performance evaluations for all sub-criteria are either numbers or words. How to aggregate all of these data without losing information is a very daunting task using a type-1 fuzzy set (T1 FS) approach. This paper applies a new methodology—Perceptual Computer (Per-C)—to help solve this hierarchical multi-person multi-criteria decision making problem. The Per-C has three components: encoder, computing with words (CWW) engine and decoder. First, the interval approach (IA) is used to obtain interval type-2 fuzzy set (IT2 FS) word models for the words in a pre-specified vocabulary. Second, a linguistic weighted average (LWA) is used to aggregate all the data including numbers and words modeled by IT2 FSs. Finally, a centroid-based ranking method is used to rank the location choices, and a similarity measure is used to obtain similarities of the location choices. The decision-maker decides the winning location choice as the one with the highest ranking and least similarity to other locations.     

The transfer point location problem

In this paper, we introduce the transfer point location problem. Demand for emergency service is generated at a set of demand points who need the services of a central facility (such as a hospital). Patients are transferred to a helicopter pad (transfer point) at normal speed, and from there they are transferred to the facility at increased speed. The general model involves the location of p helicopter pads and one facility. In this paper, we solve the special case where the location of the facility is known and the best location of one transfer point that serves a set of demand points is sought. Both minisum and minimax versions of the models are investigated. In follow up papers we investigate the general model using the results obtained in this paper.