基于改进的GRA-PDEA模型的应急系统优化选址

从应急系统优化选址的实践需求出发,构建了多输入/多输出、多种数据类型的决策指标体系,给出了针对成本/效益指标的区间型、模糊型属性值的规范化处理模型,得到各备选方案的指标属性值规范化矩阵.采用了带决策者偏好的数据包络分析模型进行优化选址决策,体现了在应急系统优化选址问题中应注重的相对有效性决策策略,同时引入基于灰色关联分析的定权模型,使决策过程既发挥决策者的主观能动性,又规避其主观臆断.通过给出备选方案的实证分析,较好地实现了应急系统优化选址的目的,选址结果与实际情况也是相吻合的.     

鲁棒动态设施选址问题的近似算法

设施选址问题是组合优化中重要问题之一。动态设施选址问题是传统设施选址问题的推广,其中度量空间中设施的开设费用和顾客的需求均随着时间的变化而变化。更多地,经典设施选址问题假设所有的顾客都需要被服务。在这个模型假设下,所有的顾客都需要服务。但事实上,有时为服务距离较远的顾客,需要单独开设设施,导致了资源的浪费。因此,在模型设置中,可以允许一些固定数目的顾客不被服务 (带异常点的设施选址问题),此外也可以通过支付一些顾客的惩罚费用以达到不服务的目的 (带惩罚的设施选址问题)。本文将综合以上两种鲁棒设置考虑同时带有异常点和惩罚的动态设施选址问题,通过原始-对偶框架得到近似比为3的近似算法。     

需求导向的容量设施竞争选址问题研究

客户意愿与容量限制是竞争设施选址问题中两个重要的影响因素,在考虑客户意愿与设施容量共同作用条件下,建立了最小化企业总成本以及每个客户费用为目标的竞争设施选址问题优化模型,通过设计需求导向服务分配机制解决设施与客户之间服务关系分配问题,结合模拟退火思想提出了求解模型的算法。最后利用数值例子分析了需求导向服务分配机制以及目标权重、预算限额等参数对于选址决策的影响,其中考虑需求导向因素会适当增加企业的总成本,但可以减少客户所付出的费用从而增强对客户的吸引力;另外企业的预算限额对于企业的设施选址决策有着重要的影响,企业所能获取的市场份额与其选址预算限额呈正相关的关系;而客户所需付出的总费用与企业提供服务的总成本两者之间则呈负相关的关系,因此需要通过服务质量与成本之间的权衡实现最理想的选址决策。     

带时效性约束的配送中心多源选址问题研究

应用启发式算法求解带时效性约束的多源选址问题.分析物流配送的时效性问题,建立带时效性约束的配送中心多源选址模型.构造两步启发式算法:1)借助传统迭代算法,求解物流服务分配矩阵,把多源选址问题转化为单源选址问题;2)基于M ATLAB函数,设计优化程序,计算带时效性约束的单源选址模型.并给出算例,验证模型和算法的可行性.研究表明两步启发式算法是求解带时效性约束的物流配送中心多源连续选址问题的有效算法.     

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.     

区间图上可带负权的2-中位选址问题

本文研究了区间图上可带负权的2-中位选址问题.根据目标函数的不同,可带负权的$p-$中位选址问题($p\geq 2$)可分为两类：即 MWD 和 WMD 模型;前者是所有顶点与服务该顶点的设施之间的最小权重距离之和,后者是所有顶点与相应设施之间的权重最小距离之和.在本篇论文中,我们讨论了区间图上可带负权2-中位选址问题的两类模型,并分别设计时间复杂度为$O(n^2)$的多项式时间算法.     

区间图上可带负权的2-中位选址问题（英文）

Abstract本文研究了区间图上可带负权的2-中位选址问题.根据目标函数的不同,可带负权的p-中位选址问题（p≥2）可分为两类：即MWD和WMD模型;前者是所有顶点与服务该顶点的设施之间的最小权重距离之和,后者是所有顶点与相应设施之间的权重最小距离之和.在本篇论文中,我们讨论了区间图上可带负权2-中位选址问题的两类模型,并分别设计时间复杂度为O（n~2）的多项式时间算法.     

基于可信度模糊费用多设施选址模型和算法

设施选址在整个物流网络中是一个十分重要的决策问题，它决定了整个物流系统的模式，结构和形状。设施选址方法尤其是多设施选址方法的研究已经成为一个备受人们关注的研究领域。本文首先介绍了设施选址的重要性，然后在模糊环境中根据不同的决策标准，建立了三种不同类型的模型，并设计了一个遗传算法来解决其中一个模型。最后给出了一个数值例子。     

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。     

带退货和软时间窗的多仓库选址-路径问题研究

选址-路径问题(location routing problems, LRP)是集成物流网络研究中的难题,也是任何一个大型物流配送企业必须面对的管理决策问题。本文在仓库容量约束和车辆容量约束的基础上,结合送取货一体化的配送模式和客户服务时间要求,建立了带退货和软时间窗的多仓库选址-路径(MDLRP)数学模型。针对MDLRP问题求解的复杂性,引入局部搜索算法和重组策略,设计了自适应混合遗传算法,对模型进行整体求解。最后进行数值实验,表明本文提出的模型和改进算法具有实用性和优越性,可为选址和车辆运输决策提供重要参考依据。     

生鲜农产品多配送中心连续选址FCM-ISA算法及应用

本文对生鲜农产品多配送中心连续选址问题进行了研究,在建立考虑最小距离约束下连续选址模型的基础上,针对以往连续选址模型求解过程中采用随机方式生成初始解会造成算法搜索范围过大且易陷入局部最优的局限,创新性地提出了连续选址模型的模糊C均值聚类-改进模拟退火(FCM-ISA)算法,并以杭州市为例验证了所建模型及设计算法的有效性。计算结果表明,本文所建立的生鲜农产品多配送中心连续选址模型更符合实际选址情景,设计的FCM-ISA算法收敛速度快且全局寻优效果好,对科学地进行生鲜农产品多配送中心选址决策具有重要的指导意义。     

Obnoxious-facility location and data-envelopment analysis: A combined distance-based formulation

We have broadened the classic anti-center models to include generalized-distance measures. It includes in the inherent proximity measures other cost/benefit metrics. Unlike classic data envelopment analysis (DEA), the combined location/DEA model proposed here assumes disposability of input/output's only. It represents a more flexible formulation. The locations of multiple sites are analyzed using a binary integer program, while evaluation is performed by the full strength of a DEA model. Through a case study, we show how location and DEA models can be used together to more realistically characterize a siting decision.     

Hotelling's duopoly on a tree

This paper considers Hotelling's duopoly model on a tree. It is shown that if both competitors have price and location as decision variables, no equilibrium exists. If prices are fixed in advance by the competitors, equilibria may exist. Conditions for this case are developed. Then the related sequential location problem is investigated. It is shown that it is usually beneficial for a facility not to locate first but to react to its competitor's location choice.     

A memetic algorithm for multi-objective dynamic location problems

This paper describes a new multiobjective interactive memetic algorithm applied to dynamic location problems. The memetic algorithm integrates genetic procedures and local search. It is able to solve capacitated and uncapacitated multi-objective single or multi-level dynamic location problems. These problems are characterized by explicitly considering the possibility of a facility being open, closed and reopen more than once during the planning horizon. It is possible to distinguish the opening and reopening periods, assigning them different coefficient values in the objective functions. The algorithm is part of an interactive procedure that asks the decision maker to define interesting search areas by establishing limits to the objective function values or by indicating reference points. The procedure will be applied to some illustrative location problems.     

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.     

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。     

基于改进NSGA-II算法的多级服务设施备用覆盖选址决策模型

为了应对跨区域突发事件过程中受灾点服务差异化需求的问题,建立了应急储备设施点的多级备用覆盖选址决策模型,即一个需求点由多个应急设施提供不同质量水平的服务,并考虑设施繁忙状态下由其他设施点提供服务的状况,使模型更加符合实际应用。首次通过设计分段的染色体编码方式改进NSGA-II算法提升运算效率以更好地解决多目标选址决策问题,将改进方法下得到的Pareto解分布与NSGA-II算法下的仿真结果进行对比分析,结合设施点的部署策略得到不同的空间布局方案。证明了模型的可行性及改进NSGA-II算法在解决设施点多目标选址决策问题时的有效性。     

Tools of the mind: Techniques and methods for intellectual work: V. STIBIC North-Holland,Amsterdam, 1982, xiii + 297 pages,Dfl.85.00

Many location problems may be separated into a series of interrelated macro, meso and micro decision-making states. The macro scale decision determines the type, capacity and number of facilities, the meso scale decision determines the location and allocation of facilities and the micro scale decision determines such considerations as routing and scheduling of service vehicles. This paper concerns the first two levels of decision-making.The present paper demonstrates the use of two models: (i) an analytical model that uses continuum approximations and methods of calculus to determine the number of facilities, the capacity and the approximate location of each that minimizes the sum of the transportation and facility costs for a slowly varying demand rate, and (ii) a traditional location-allocation model that determines more exactly the resulting locations and allocations. These two approaches have specific requirements in terms of data input, cost of data collection and cost of solution and, consequently, yield unique insights and benefits for practising planners. The strengths and weaknesses of the two models are complementary. This thesis is developed with an analysis of the Calgary, Alberta refuse collection and disposal system.     

铁路应急设施非概率可靠性选址优化研究

为解决小样本、贫信息下铁路应急资源储备点的可靠性选址问题,创新性地将选址-路径问题与区间非概率可靠性方法结合起来,考虑灾情发生后应急设施点在可接受的时间范围内响应受灾点的需求能力及其稳定程度,采用区间值度量路段阻抗,基于区间非概率可靠性理论及区间运算规则,提出路径的非概率可靠性度量及可靠最短路径选择方法;建立基于区间时间阻抗下可靠最短路径的无容量设施选址模型,提出约束条件限制的Monte Carlo改进算法,确定了铁路资源储备点选址的最优方案。实例表明,本文的优化方案能更好地保证救援的时间可靠性,改进的求解算法具有更小的时间复杂度,有效地缩短了运算时间,改善了解的质量。本文的方法与模型体系对于实现铁路应急设施可靠性选址,为决策者提供决策支持,提高铁路应急响应能力具有重要的指导意义。     

QUANTITATIVE METHODS FOR DECISION SUPPORT IN THE ICELANDIC FISHING INDUSTRY

Abstract Modern fisheries already collect vast amount of data, for example, through ERP systems and electronic log‐books. It is however well known that the data are rarely used for improving operational decision making. By converting this data into useable information, decision making in the fishing industry could be improved. This paper attempts to show that quantitative methods can be of use in many aspects of decision making in the fishing industry. The paper proposes a hierarchically structured decision support process based on two different optimization models for supporting the long‐ and short‐term decision making in fisheries. For long‐term planning the paper proposes a linear optimization model that describes the entire operation of a vertically integrated seafood company. For short‐term decision making the paper proposes a mixed integer linear optimization model to assist in organizing vessel trips and deciding catch location with regard to raw material quality and yield obtained in processing.