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。     

A Probabilistic Minimax Location Problem on the Plane

In this paper we consider the weighted minimax (1-center) location problem in the plane when the weights are not given but rather drawn from independent uniform distributions. The problem is formulated and analyzed. For certain parameters of the uniform distributions the objective function is proven to be convex and thus can be easily solved by standard software such as the Solver in Excel. Computational experience is reported.     

COBRA: A New Formulation of the Classic p-Median Location Problem

The p-median problem was first formulated as an integer-linear programming problem by ReVelle and Swain (1970) and further revised by Rosing, ReVelle and Rosing-Vogelaar (1979). These two forms have withstood the test of time, as they have been used by virtually everyone since then. We prove that a property associated with geographical proximity makes it possible to eliminate many of the model variables through a substitution process. This new substitution technique has resulted in the elimination of up to 60% of the variables needed in either of these classic model formulations.     

Spherical Minimax Location Problem

This paper presents an algorithm for determining a minimax location to service demand points that are equally weighted and distributed over a sphere. The norm under consideration is geodesic. The algorithm presented here is based on enumeration and has a polynomial time complexity.     

基于偏正态分布联合位置、尺度与偏度模型的极大似然估计

本文提出了基于偏正态分布联合位置、尺度与偏度模型,通过极大似然迭代算法给出了联合模型参数的估计方法,最后通过随机模拟和实例研究说明了提出的模型与方法的有效性。     

A Lagrangean Heuristic for a Modular Capacitated Location Problem

This paper considers the Modular Capacitated Location Problem (MCLP) which consists of finding the location and capacity of the facilities, to serve a set of customers at a minimum total cost. Each customer has an associated demand and the capacity of each potential location must be chosen from a finite and discrete set of available capacities. Practical applications of this problem can be found in the location of warehouses, schools, health care services or other types of public services. For the MCLP different mixed integer linear programming models are proposed. The authors develop upper and lower bounds on the problem's optimal value and present computational results with randomly generated tests problems.     

The Maximin-Maxisum Network Location Problem

In this paper, we consider the problem of finding a point on a general network using two objectives, maximizing the minimum weighted distance from the point to the vertices (Maximin) and maximizing the sum of weighted distances between the point and the vertices (Maxisum). This bicriterion model can be used to locate an obnoxious facility on a network. We will identify the model properties, develop a polynomial algorithm for generating the efficient set and provide a numerical example.     

On the Inverse Problem for Robust Capture Zone Construction

An interception problem with variable velocities and variable lateral acceleration boundaries is considered. Two problems, inverse to constructing the capture zone for a given linear strategy, are formulated. In the first (weak) formulation, a linear strategy is derived forcing its capture zone to contain a given set. In the second (strong) formulation, the capture zone of such a linear strategy is forced to coincide with a given set. A step-by-step algorithm, solving these problems, is derived. This algorithm is based on a detailed differential-geometrical analysis of the capture zone boundary. Illustrative examples are presented.     

一类应急服务设施选址问题的模型及算法

在分析城市应急服务设施选址问题基础上,建立了限定期条件下应急服务设施选址问题的数学模型,提出了一种基于遗传算法的应急服务设施选址模型的有效算法,并通过算例分析验证了该方法的有效性.     

灾后重建地区新增血站的选址问题研究

根据灾后重建地区血液保障体系建设的实际情况,考虑血站间的依附系数对血站布局的影响,建立了一种p-中值模型用来解决新增血站的选址问题,并设计了一种遗传-禁忌混合算法对模型进行求解。之后以汶川大地震灾区——四川省阿坝州为例进行了实例分析,得到了不同p值与依附系数下的新增血站选址方案,以期为相关部门规划灾后重建地区的血液保障体系提供理论依据与决策参考。     

An Improved Branch & Bound Method for the Uncapacitated Competitive Location Problem

In this paper, the problem of locating new facilities in a competitive environment is considered. The problem is formulated as the firm expected profit maximization and a set of nodes is selected in a graph representing the geographical zone. Profit depends on fixed and deterministic location costs and, since customers are independent decision-makers, on the expected market share. The problem is an instance of nonlinear integer programming, because the objective function is concave and submodular. Due to this complexity a branch & bound method is developed for solving small size problems (that is, when the number of nodes is less than 50), while a heuristic is necessary for larger problems. The branch & bound is called data-correcting method, while the approximate solutions are obtained using the heuristic-concentration method.     

The Tree of Hubs Location Problem

This paper presents the Tree of Hubs Location Problem. It is a network hub location problem with single assignment where a fixed number of hubs have to be located, with the particularity that it is required that the hubs are connected by means of a tree. The problem combines several aspects of location, network design and routing problems. Potential applications appear in telecommunications and transportation systems, when set-up costs for links between hubs are so high that full interconnection between hub nodes is prohibitive. We propose an integer programming formulation for the problem. Furthermore, we present some families of valid inequalities that reinforce the formulation and we give an exact separation procedure for them. Finally, we present computational results using the well-known AP and CAB data sets.     

两阶段选址优化问题研究

本文主要考虑如下实际问题:假设选址决策者需要建设p个设施,但是由于资金等等的影响,实际建设时会被要求先建设q个设施,其次再建设p-q个设施(设p>q),同时要求,在建设p-q个设施的时候,已经建设好的q个设施不被删除。本文建立了一个两阶段优化问题,问题的输出是两个待修建的设施的集合Fq,Fp,|Fp|=p,|Fq|=q,且Fq是Fp的子集,问题的目标是最小化这两个设施集合的费用同对应的最优费用的比值的最大值。本文给出一个近似比为9的近似算法,并对一些特殊的情况进行了讨论。所得结论对实际的选址决策具有理论意义,同时也完善已有相关研究结果。     

考虑共享不确定因素的应急设施最大覆盖选址模型

为提升应急设施的服务质量和抵御中断风险的能力,研究应急设施最大覆盖选址-分配决策问题。扩展无容量限制的固定费用的可靠性选址决策模型,建立考虑共享不确定因素的应急设施最大覆盖选址优化模型,通过在目标和约束中引入budget不确定集刻画共享不确定因素,基于Bertsimas和Sim鲁棒优化方法建立混合整数规划模型,并将非线性问题转化为易于求解的鲁棒等价模型,利用带混沌搜索策略的改进灰狼优化算法求解模型,并对不确定鲁棒水平和中断概率进行敏感性分析。最后通过案例及数据仿真结果的对比分析,验证了模型的合理性和有效性,并给出最优的选址分配布局。     

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。     

基于加权绝对值距离Steiner最优树的选址问题

提出基于加权绝对值距离Steiner最优树思想的选址模型,给出了该模型的蚂蚁算法实现策略.在此基础上,分析了电子商务环境下企业配送中心选址问题,并用算例验证了该选址方案的可行性.     

双会议服务器选址问题研究

中位选址问题一直是管理学科的研究热点,本文考虑平面点集选址问题中的双会议服务器选址问题,该问题可以看成是2中位问题的衍生问题。令P为平面上包含n个点的点集,双会议服务器选址问题即为寻找由该点集构成的一棵二星树,使得这棵树上所有叶子之间的距离和最小。本文给出求解该问题的关键几何结构和最优解算法设计,并证明所给算法时间复杂性为O(n³logn)。     

半讨厌型设施选址问题的模型与算法

研究了结合网络和平面模型的半讨厌型设施的选址问题.半讨厌型设施结合了讨厌型设施与喜爱型设施的性质,一方面由于这些设施对人们带来很多副作用,人们想要远离他们以避免遭到污染,但同时人们又希望距离设施不要过远,因此建立0-1整数模型,在保证所有人使用该设施的距离不超过既定距离的基础上,使污染范围最小.由于该问题是NP困难问题,本为给出了启发式算法,通过算例进行了比较分析,证明了算法的有效性.     

A Genetic Algorithm Based Approach for the Uncapacitated Continuous Location–Allocation Problem

A GA-based approach is introduced to address the continuous location–allocation problem. Selection and removal procedures based on groups of chromosomes instead of individual chromosomes are put forward and specific crossover and mutation operators that rely on the impact of the genes are proposed. A new operator that injects once in a while new chromosomes into the population is also introduced. This provides diversity within the search and attempts to avoid early convergence. This approach is tested on existing data sets using several runs to evaluate the robustness of the proposed GA approach.