带惩罚的容错设施布局问题的近似算法

在带惩罚的容错设施布局问题中, 给定顾客集合、地址集合、以及每个顾客和各个地址之间的连接费用, 这里假设连接费用是可度量的. 每位顾客有各自的服务需求, 每个地址可以开设任意多个设施, 顾客可以被安排连接到某些地址的一些开设的设施上以满足其需求, 也可以被拒绝, 但这时要支付拒绝该顾客所带来的惩罚费用. 目标是确定哪些顾客的服务需求被拒绝并开设一些设施, 将未被拒绝的顾客连接到不同的开设设施上, 使得开设费用、连接费用和惩罚费用总和最小. 给出了带惩罚的容错设施布局问题的线性整数规划及其对偶规划, 进一步, 给出了基于其线性规划和对偶规划舍入的4-近似算法.     

带次模惩罚和随机需求的设施选址问题

考虑带次模惩罚和随机需求的设施选址问题,目的是开设设施集合的一个子集,把客户连接到开设的设施上并对没有连接的客户进行惩罚,使得开设费用、连接费用、库存费用、管理费用和惩罚费用之和达到最小. 根据该问题的特殊结构,给出原始对偶3-近似算法. 在算法的第一步,构造了一组对偶可行解;在第二步中构造了对应的一组原始整数可行解,这组原始整数可行解给出了最后开设的设施集合和被惩罚的客户集合. 最后,证明了算法在多项式时间内可以完成,并且算法所给的整数解不会超过最优解的3倍.     

平方度量的k层设施选址问题的近似算法

本文中,我们研究平方度量的k层设施选址问题,该问题中设施分为k层,每个顾客都要连接到位于不同层上的k个设施,顾客与设施以及设施与设施之间的距离是平方度量的.目标是使得开设费用与连接费用之和最小.基于线性规划舍入技巧,我们给出了9-近似算法.进一步,我们研究了平方度量的k层软容量设施选址问题,并给出了线性规划舍入12.2216-近似算法.     

软容量约束的动态设施选址问题的近似算法

考虑软容量约束的动态设施选址问题.假设设施的开放费用及连接费用都与时间有关,而且每一个设施均有容量约束.对此问题给出了第一个近似比为6的原始对偶(组合)算法.运行贪婪增加程序后,近似比进一步改进到3.7052.     

带有异常点的平方度量设施选址问题

传统的设施选址问题一般假设所有顾客都被服务,考虑到异常点的存在不仅会增加总费用（设施的开设费用与连接费用之和）,也会影响到对其他顾客的服务质量。研究异常点在最终方案中允许不被服务的情况,称之为带有异常点的平方度量设施选址问题。该问题是无容量设施选址问题的推广。问题可描述如下：给定设施集合、顾客集,以及设施开设费用和顾客连接费用,目标是选择设施的子集开设以满足顾客的需求,使得设施开设费用与连接费用之和最小。利用原始对偶技巧设计了近似算法,证明了该算法的近似比是9。     

随机容错设施布局问题的近似算法

在确定性的容错设施布局问题中, 给定顾客的集合和地址的集合. 在每个地址上可以开设任意数目的不同设施. 每个顾客j有连接需求r_j. 允许将顾客j连到同一地址的不同设施上. 目标是开设一些设施并将每个顾客j连到r_j个不同的设施上, 使得总开设费用和连接费用最小. 研究两阶段随机容错设施布局问题(SFTFP), 顾客的集合事先不知道, 但是具有有限多个场景并知道其概率分布. 每个场景指定需要服务的顾客的子集. 并且每个设施有两种类型的开设费用. 在第一阶段根据顾客的随机信息确定性地开设一些设施, 在第二阶段根据顾客的真实信息再增加开设一些设施．给出随机容错布局问题的线性整数规划和基于线性规划舍入的5-近似算法.     

不确定条件下的乡村中小学布局优化

学校的合理规划布局是实现教育资源优化配置、提高办学效益和推动教育均衡发展的重要途径。已有许多学者研究了学校的布局问题,但基本上都忽略了交通网络条件以及不确定因素对学校布局的影响。本研究将在前人研究基础上,重点考虑交通网络对乡村中小学选址的影响,并假设旅行时间具有不确定性,从而以最小化学生旅行成本、学校建设、道路修建和道路升级成本为目标,构建不确定条件下的设施区位设计模型。在算法求解方面提出混合模拟退火算法,用于确定新建学校的最佳位置,以及新道路的修建和原有道路的升级情况。最后,将提出的模型和算法应用到实际案例中。     

泄洪设施修建计划的数学模型

某乡政府计划解决防汛水利设施建设问题,即通过开挖小型排洪沟与修建新的泄洪河道来满足防汛需要.针对该乡的泄洪设施修建计划,主要研究以下三个问题:(1)给出同时开挖给定的8条小型排洪沟和新建一条给定的泄洪河道的最优修建方案;(2)已知该乡各村之间新建泄洪河道的长度,给出一个在各村之间互通的另一新泄洪河道的网络修建计划,使之达到可泄洪量100万立方米/小时;(3)当新泄洪河道网络修建完后,安排人员进行维护工作,研究维护人员在各村留宿的概率分布.在费用最省的目标下,建立了问题(1)和问题(2)的数学规划模型,并得到泄洪设施的最优修建方案.应用Markov链及转移概率矩阵等知识,建立了问题(3)的等概率和非等概率的两种数学模型,并得知维护人员在各村留宿的概率分布是稳定的.     

带惩罚的动态设施选址问题的近似算法

本文研究带惩罚的动态设施选址问题,在该问题中假设不同时段内设施的开放费用、用户的需求及连接费用可以不相同,而且允许用户的需求不被满足,但是要有惩罚.对此问题我们给出了第-个近似比为1.8526的原始对偶(组合)算法.     

基于SA算法的应急公共服务设施布局优化研究——以上海市长宁区应急避难场所为例

近年来,随着城市的发展以及各类突发事件频繁发生,城市中的应急服务需求不断增加,为了减少事故灾害带来的生命财产的损失,政府部门高度重视应急公共服务设施的建设.以上海市长宁区应急避难场所为研究对象,构建多目标函数,确定约束条件,利用模拟退火算法对应急避难场所配置空间布局进行优化,得到最优配置方案,并通过斑块邻近度(PPI)、斑块凝聚度(PCI)及聚集指数(AI)的计算分析了空间布局的合理性,以及应急避难场所与人口分布的协调性.研究对于应急公共服务设施配置布局的科学性和合理性,完善应急公共服务设施配置布局理论,具有较大的理论意义和实践意义,同时也为政府和相关城市规划工作者在对应急公共服务设施的配置及选址布局优化方面提供决策和依据.     

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。     

Algorithms for the generalized quadratic assignment problem combining Lagrangean decomposition and the Reformulation-Linearization Technique

In this paper, we propose two exact algorithms for the GQAP (generalized quadratic assignment problem). In this problem, given M facilities and N locations, the facility space requirements, the location available space, the facility installation costs, the flows between facilities, and the distance costs between locations, one must assign each facility to exactly one location so that each location has sufficient space for all facilities assigned to it and the sum of the products of the facility flows by the corresponding distance costs plus the sum of the installation costs is minimized. This problem generalizes the well-known quadratic assignment problem (QAP). Both exact algorithms combine a previously proposed branch-and-bound scheme with a new Lagrangean relaxation procedure over a known RLT (Reformulation-Linearization Technique) formulation. We also apply transformational lower bounding techniques to improve the performance of the new procedure. We report detailed experimental results where 19 out of 21 instances with up to 35 facilities are solved in up to a few days of running time. Six of these instances were open.     

Approximation algorithm for facility location with service installation costs

In this paper, we study the uncapacitated facility location problem with service installation costs depending on the type of service required. We propose a polynomial-time approximation algorithm with approximation ratio 1.808 which improves the previous approximation ratio of 2.391 of Shmoys, Swamy, and Levi.     

Design and analysis of hybrid metaheuristics for the Reliability p-Median Problem

In the p-Median Problem, it is assumed that, once the facilities are opened, they may not fail. In practice some of the facilities may become unavailable due to several factors. In the Reliability p-Median Problem some of the facilities may not be operative during certain periods. The objective now is to find facility locations that are both inexpensive and also reliable. We present different configurations of two hybrid metaheuristics to solve the problem, a genetic algorithm and a scatter search approach. We have carried out an extensive computational experiment to study the performance of the algorithms and compare its efficiency solving well-known benchmark instances.     

带有线性惩罚的鲁棒k-种产品设施选址问题的近似算法

$k$-种产品设施选址问题是指存在一组客户和一组可以建设设施的地址。现有$k$种不同的产品,每一客户均需要$k$种不同的产品,且每一设施最多只能生产一种产品。问题的要求是从若干地址中选择一组地址来建立设施,对所要建立的设施指定其生产的产品,并为每一个客户提供一组指派确保每一客户都有$k$个设施来为其提供$k$种不同的产品,使得设施建设费用与运输费用之和最小。对于$k$-种产品设施选址问题,我们通常简写为$k$-PUFLP,其中,当所有设施建设费用为0时,记为$k$-PUFLPN。本文对$k$-PUFLPN进行线性舍入,通过分析最优分数解特殊结构,当$k\geq 3$时分析算法将$k$-PUFLPN的近似比从$\frac{3k}{2}-1$提升到了$\frac{3k}{2}-\frac{3}{2}$。鲁棒$k$-种产品设施选址问题是指在该问题中,最多有$q$个客户可以不被服务。我们首次对无容量限制下建设费用为0时的鲁棒$k$-种产品选址问题建立模型,当$k\geq 3$,得到了$\frac{3k}{2}-\frac{3}{2}$近似算法。对顾客伴有线性惩罚的鲁棒$k$-种产品设施选址问题,本文同时考虑异常值与惩罚性,利用$k$-PUFLPN中最优整数解与最优分数解的关系,得到了$\frac{3k}{2}-\frac{3}{2}$近似算法。     

Simulated N-Body: New Particle Physics-Based Heuristics for a Euclidean Location-Allocation Problem

The general facility location problem and its variants, including most location-allocation and P-median problems, are known to be NP-hard combinatorial optimization problems. Consequently, there is now a substantial body of literature on heuristic algorithms for a variety of location problems, among which can be found several versions of the well-known simulated annealing algorithm. This paper presents an optimization paradigm that, like simulated annealing, is based on a particle physics analogy but is markedly different from simulated annealing. Two heuristics based on this paradigm are presented and compared to simulated annealing for a capacitated facility location problem on Euclidean graphs. Experimental results based on randomly generated graphs suggest that one of the heuristics outperforms simulated annealing both in cost minimization as well as execution time. The particular version of location problem considered here, a location-allocation problem, involves determining locations and associated regions for a fixed number of facilities when the region sizes are given. Intended applications of this work include location problems with congestion costs as well as graph and network partitioning problems.     

考虑应急设施中断风险与防御的可靠性选址模型研究

为提高应急设施运行的可靠性和抵御中断风险的能力, 研究中断情境下的应急设施选址-分配决策问题。扩展传统无容量限制的固定费用选址模型, 从抵御设施中断的视角和提高服务质量的视角建立选址布局网络的双目标优化模型, 以应急设施的建立成本和抵御设施中断的加固成本最小为目标, 以最大化覆盖服务质量水平为目标, 在加固预算有限及最大最小容量限制约束下, 构建中断情境下应急设施的可靠性选址决策优化模型。针对所构建模型的特性利用非支配排序多目标遗传算法(NSGA-Ⅱ)求解该模型, 得到多目标的Pareto前沿解集。以不同的算例分析和验证模型和算法的可行性。在获得Pareto前沿的同时对不同中断概率进行灵敏度分析, 给出Pareto最优解集的分布及应急设施选址布局网络的拓扑结构。     

An improved Benders decomposition algorithm for the logistics facility location problem with capacity expansions

We investigate a logistics facility location problem to determine whether the existing facilities remain open or not, what the expansion size of the open facilities should be and which potential facilities should be selected. The problem is formulated as a mixed integer linear programming model (MILP) with the objective to minimize the sum of the savings from closing the existing facilities, the expansion costs, the fixed setup costs, the facility operating costs and the transportation costs. The structure of the model motivates us to solve the problem using Benders decomposition algorithm. Three groups of valid inequalities are derived to improve the lower bounds obtained by the Benders master problem. By separating the primal Benders subproblem, different types of disaggregated cuts of the primal Benders cut are constructed in each iteration. A high density Pareto cut generation method is proposed to accelerate the convergence by lifting Pareto-optimal cuts. Computational experiments show that the combination of all the valid inequalities can improve the lower bounds significantly. By alternately applying the high density Pareto cut generation method based on the best disaggregated cuts, the improved Benders decomposition algorithm is advantageous in decreasing the total number of iterations and CPU time when compared to the standard Benders algorithm and optimization solver CPLEX, especially for large-scale instances.     

Integrated scheduling of production and distribution for manufacturers with parallel batching facilities

We consider a class of integrated scheduling problems for manufacturers. The manufacturer processes job orders and delivers products to the customer. The objective is to minimize the service span, that is, the period lasting from the time when the order is received to the time when all the products have been delivered to the customer. In the production phase, parallel batch-processing facilities are used to process the jobs. Jobs have arbitrary sizes and processing times. Each facility has a fixed capacity and jobs are processed in batches with the restriction that the total size of jobs in a batch does not exceed the facility capacity. When all the jobs in a batch are completed, the batch is completed. In the distribution phase, the manufacturer uses a vehicle with a fixed capacity to deliver products. The transportation time from the manufacturer to the customer is a constant. Completed products can be delivered in one transfer if the total size does not exceed the vehicle capacity. We first consider the problem where jobs have the same size and arbitrary processing times. We propose approximation algorithms for the problem and we show that a worst-case ratio performance guarantee is respectively 2–1/m. Then we consider the problem where jobs have the same processing time and arbitrary sizes. An approximation algorithm is proposed with an absolute worst-case ratio of 13/7 and an asymptotic worst-case ratio of 11/9. Both the proposed algorithms can be executed in polynomial time.