Fractional location problems

In this paper we analyze some variants of the classical uncapacitated facility location problem with a ratio as an objective function. Using basic concepts and results of fractional programming, we identify a class of one-level fractional location problems which can be solved in polynomial time in terms of the size of the problem. We also consider the fractional two-echelon location problem, which is a special case of the general two-level fractional location problem. For this two-level fractional location problem we identify cases for which its solution involves decomposing the problem into several one-level fractional location problems.     

基于仿射传播聚类的大规模选址布局问题求解*

选址布局问题是一个广泛研究的运筹学问题。通过将选址布局问题看做聚类问题,结合仿射传播聚类算法并且将候选地址的信息映射为特征向量,提出了两种求解选址布局问题的方法：基于块划分的选址布局方法和基于道路网络的选址布局方法。使用模拟数据集和真实数据集来评估两种方法,实验结果表明两种方法都能够求解设施资源受限和不受限情况下的选址布局问题,而且可以很好地解决大规模的选址布局问题。     

Optimal location policy for three competitive facilities

Competitive facility location problems have been investigated in many papers. In most, authors have applied location models with two competitors. In this paper three companies, which are mutually competitive, intend to locate their facilities in a linear market. It is well-known that Nash equilibrium solution for location problem does not include three competitive facilities. In this paper we present the optimal location strategies for three facilities. In our model we assume that the demands are continuously distributed in a linear market and the facilities are locating according to a specific order of sequence, A, B and C. We apply the Stackelberg equilibrium solutions for competitive location problems with three facilities. In our model, we consider the decision problems in three stages. In the first stage, we decide the optimal location of facility A, which is located optimally in respect to the remaining two facilities B and C. In the second stage, we determine the optimal location of facility B which is optimally located in respect to facility C, by utilizing the information on the location of facility A. Finally in the third stage problem we decide the location of facility C, optimally located by utilizing the information on the location of A and B. In the first stage, we need the optimal solutions of the second and third stages. In the second stage we need the optimal solution of the third stage problem. Therefore, first we solve the third stage problem which is the simplest. After that, we solve the second stage problem utilizing the optimal solution strategy of the third stage problem. In this paper we present the optimal location strategies for three facilities.     

The structured total least squares algorithm research for passive location based on angle information

Based on the constrained total least squares (CTLS) passive location algorithm with bearing-only measurements, in this paper, the same passive location problem is transformed into the structured total least squares (STLS) problem. The solution of the STLS problem for passive location can be obtained using the inverse iteration method. It also expatiates that both the STLS algorithm and the CTLS algorithm have the same location mean squares error under certain condition. Finally, the article presents a kind of location and tracking algorithm for moving target by combining STLS location algorithm with Kalman filter (KF). The efficiency and superiority of the proposed algorithms can be confirmed by computer simulation results.     

Dynamic Location and Entry Mode Selection of Multinational Manufacturing Facilities under Uncertainty: A Chance-constrained Goal Programming Approach

As the global marketplace continues to expand, the firm's location strategy should shift from domestic to international. An international location problem is different from the traditional domestic location problem in that the former is influenced by a greater variety of uncontrollable, unpredictable, and dynamic factors than is the latter. These factors may include political conditions, expropriation risks, trade regulations, currency exchange rates, cultural differences, and global distribution channel structures. Consequently, the international location problem is more diverse, volatile and complex. Nevertheless, a vast majority of the location literature overlooked many important international aspects. To help the multinational firm formulate viable location strategies in the changing world marketplace, this paper proposes multiple-period, multiple-plant, multiple-objective, and stochastic location model.     

网上数据库的选址问题

文章主要分析在一个通信网络中数据库如何分布,分布多少,才能使总费用最低,并建立了相应的数据库选址模型。     

在非视距传播环境下无线定位的AOA算法

非视距传播(NLOS)是蜂窝无线定位的一个关键的问题,要提高无线定位的精度,必须有效减小非视距传播的影响.基于一种适合对各种定位算法进行分析的基于几何结构的单次反射统计信道模型(GBSB),提出一种减小非视距传播影响的AOA定位算法,该算法利用临近基站与移动台构成的三角函数关系和波达方向的最大角度扩展作为优化的约束条件,将基于波达方向(AOA)的无线定位问题转化为有约束的最优化问题,从而提高了无线定位的精度.仿真结果证明了该算法的有效性.     

群智能算法在气体源定位中的应用综述

近几年频繁发生的气体泄漏事件使得气体源定位成为了公共安全领域亟待解决的问题。气体源定位问题本质上可以转化为最优化问题,群智能算法作为一种高效的优化算法,为其提供了一个全新的解决方案。介绍了气体源定位问题的研究背景和研究现状;根据群智能算法在气体源定位中应用的研究思路和研究内容对具有代表性研究成果进行了分类综述和对比分析;对目前基于群智能算法的气体源定位研究中存在的问题和未来发展趋势进行了分析和展望,对气体源定位问题的进一步研究提供一定的参考作用。     

粒子群算法在物流中心选址中的应用

物流中心选址是物流系统规划中的重要决策问题。为了快速得到合理的物流中心选址方案,针对问题的特点给出了选址问题的模型,提出了以最小化物流成本为目标函数的粒子群优化算法,开发了模型求解的MATLAB程序,并将算法应用于求解工厂仓库选址和废弃物回收中转站选址问题。实例求解结果表明,该算法求解选址问题的性能优于精确重心法,具有良好的搜索性能和实用性。     

基于遗传算法的检测路段选择的优化

在分析交通检测点分布优化问题的现有算法的基础上，本文构造了交通检测点优化问 题的染色体表达式，建立了此问题的遗传算法．这是第一次将遗传算法应用于交通检测点分 布优化问题．实验结果表明，此算法可以有效求得交通检测点分布问题的优化解或近似优化 解，是求解交通检测点分布问题的一个较好的方法．     

ServLoc:无线传感反应网络的安全位置服务机制

为解决无线传感反应网络的安全位置服务问题,提出了一种距离无关的安全定位协议--ServLoc定位协议.在该协议中,反应器通过认证消息包、被动接收定位请求、过滤虚假信息等方法进行位置攻击防御,位置匿名和分布地确定传感器节点位置.另外也提出了一种基于表决的位置校验协议--ServLoc校验协议,并对反应器攻击的防御方法进行了初步探讨.分析说明,该协议能够有效地平衡位置欺骗攻击的成功率和定位失效率,并在网络遭受位置攻击时,仍能有效地完成安全位置服务.     

Efficient primal-dual heuristic for a dynamic location problem

In this paper the dynamic location problem with opening, closure and reopening of facilities is formulated and an efficient primal-dual heuristic that computes both upper and lower limits to its optimal solution is described. The problem here studied considers the possibility of reconfiguring any location more than once over the planning horizon. This problem is NP-hard (the simple plant location problem is a special case of the problem studied). A primal-dual heuristic based on the work of Erlenkotter [A dual-based procedure for uncapacitated facility location. Operations Research 1978;26:992–1009] and Van Roy and Erlenkotter [A dual-based procedure for dynamic facility location. Management Science 1982;28:1091–105] was developed and tested over a set of randomly generated test problems. The results obtained are quite good, both in terms of the quality of lower and upper bounds calculated as in terms of the computational time spent by the heuristic. A branch-and-bound procedure that enables to optimize the problem is also described and tested over the same set of randomly generated problems.     

基于GIS与Steiner树问题的物流配送中心选址研究

针对建立在GIS软件封装好的算法中的传统选址模型,提出Steiner树问题的选址模型,给出了该模型基于多Agent系统的启发式算法。在此基础上,将编程工具和GIS软件相结合,分析和解决了物流配送中心的选址问题。     

基于混合粒子群优化算法的DV-Hop定位算法

针对无线传感器网络节点定位技术中DV-Hop算法的不足,利用混合粒子群优化算法对DV-Hop算法的位置估计进行校正,提出了一种CCPDV-Hop算法,该方法在不需要任何额外硬件设备和通信开销基础上,将未知节点定位问题抽象为高维最优化问题,并利用混合粒子群优化算法进行求解。仿真实验结果表明,改进的DV-Hop算法与传统方法相比,定位误差显著下降,定位精度和鲁棒性都有明显提高。     

Differential evolution for solving the mobile location management

In this work we present two new approaches to solve the location management problem, respectively, based on the location areas and the reporting cells strategies. The location management problem corresponds to the management of the network configuration with the objective of minimizing the costs involved. We use the differential evolution algorithm to find the best configuration for the location areas and the reporting cells strategies, which principally considers the location update and paging costs. With this work we want to define the best values to the differential evolution configuration, using test networks and also realistic networks, as well as compare our results with the ones obtained by other authors. These two new approaches applied to this problem have given us very good results, when compared with those obtained by other authors.     

A grouped storage method for minimizing relocations in block stacking systems

When storage and retrieval times of inventories are uncertain and the storage space for the inventories is limited, it is an important problem to assign the inventories to storage spaces so that the total expected number of relocations is minimized. This paper addresses a dynamic location problem as well as a static location problem. Mathematical models are proposed for obtaining the optimal solution. To overcome the excessive computational time of optimizing methods, a genetic algorithm is suggested. Also, simple heuristic rules are suggested to solve the dynamic location problem. Performance of various solution methods are compared with each other. Received: June 2005 / Accepted: December 2005     

遗传算法在货位分配中的应用研究

本文讨论了货位分配算法。首先建立了货位分配算法的数学模型,然后提出了采用遗传算法解决这个多目标组合优化的问题。最终通过应用验证了算法的适用性。     

A stochastic set-covering location model for both ameliorating and deteriorating items

Most of the previous works on classical location models are based on the assumption that the value (or utility) of inventory remains constant over time. In this study, a special case of the stochastic set-covering location problem is studied for both ameliorating and deteriorating items. The objective of this study is to determine the minimum number of storage facilities among a discrete set of location sites so that the probability of each customer being covered is not less than a critical value. We have formulated this problem using the stochastic set-covering problem, which can be solved via the 0–1 programming method. We have also developed a computer program for this problem and the results of a set of sample problems for fish culture storage and supply center will show the impact of the ameliorating and deteriorating rates on the location problem. For further study, a graphical user-interface with visualization for input and output needs is to be developed.     

On solving unreliable planar location problems

In this paper, we generalize conventional P-median location problems by considering the unreliability of facilities. The unreliable location problem is defined by introducing the probability that a facility may become inactive. We proposed efficient solution methods to determine locations of these facilities in the unreliable location model. Space-filling curve-based algorithms are developed to determine initial locations of these facilities. The unreliable P-median location problem is then decomposed to P 1-median location problems; each problem is solved to the optimum. A bounding procedure is used to monitor the iterative search, and to provide a consistent basis for termination. Extensive computational tests have indicated that the heuristics are efficient and effective for solving unreliable location problems.Scope and purposeThis paper addresses an important class of location problems, where p unreliable facilities are to be located on the plane, so as to minimize the expected travel distance or related transportation cost between the customers and their nearest available facilities. The unreliable location problem is defined by introducing the probability that a facility may become inactive. Potential application of the unreliable location problem is found in numerous areas. The facilities to be located can be fire station or emergency shelter, where it fails to provide service during some time window, due to the capacity or resource constraints. Alternatively, the facilities can be telecommunication posts or logistic/distribution centers, where the service is unavailable due to breakdown, repair, shutdown of unknown causes. In this paper, we prescribed heuristic procedures to determine the location of new facilities in the unreliable location problems. The numerical study of 2800 randomly generated instances has shown that these solution procedures are both efficient and effective, in terms of computational time and solution quality.     

基于RSSI&DFP的无线传感器网络声源目标定位算法

声源目标定位是无线传感器网络应用研究的一个重要问题,如何在传感器节点随机分布的条件下对目标进行快速定位,并保证较高的定位精度是定位问题的一个难点,基于二维空间中声音信号传播时的能量强度指示( RSSI)将声源目标的定位问题转化为似然函数的最优化问题,利用最优化理论中的DFP方法求出目标位置的全局最优解.仿真结果表明,算...