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.     

Locating Multiple Competitive Facilities: Spatial Interaction Models with Variable Expenditures

We develop a new framework for location of competitive facilities by introducing non-constant expenditure functions into spatial interaction location models. This framework allows us to capture two key effects – market expansion and cannibalization – within the same model.We develop algorithmic approaches for finding optimal or near-optimal solutions for several models that arise from choosing a specific form of the expenditure functions.     

Validating the Gravity-Based Competitive Location Model Using Inferred Attractiveness

The attractiveness of retail facilities is an essential component of models analyzing competition among retail facilities. In this paper we introduce an innovative method for inferring retail facility attractiveness. Readily available data from secondary sources about customers' buying power and sales volumes obtained by competing retail facilities are used. The gravity-based competitive facility location model is used to predict sales. The attractiveness of the retail facilities are inferred from these data.The procedure is used to confirm the gravity competitive facility location model. Inferred attractiveness results based on empirical data from Orange County, California, were compared with an independent survey with excellent match.     

Demand Point Aggregation for Planar Covering Location Models

The covering location problem seeks the minimum number of facilities such that each demand point is within some given radius of its nearest facility. Such a model finds application mostly in locating emergency types of facilities. Since the problem is NP-hard in the plane, a common practice is to aggregate the demand points in order to reduce the computational burden. Aggregation makes the size of the problem more manageable but also introduces error. Identifying and controlling the magnitude of the error is the subject of this study. We suggest several aggregation methods with a priori error bounds, and conduct experiments to compare their performance. We find that the manner by which infeasibility is measured greatly affects the best choice of an aggregation method.     

一个带产品定价约束的竞争选址双层规划模型及其求解算法

以大型连锁卖场的选址为研究背景,提出了一个在竞争环境下使获利最大的竞争选址定价双层规划模型,其中上层模型做出选址决策,下层模型确定产品的纳什均衡价格.将设施效用引入到模型中,用指数效用函数来刻画顾客的购物行为偏好,首次证明了不合作状态下双方价格均衡解的存在性和唯一性,并给出了求解最优设施点设置方案和价格均衡解的算法思想及数值算例.     

基于DCT变换的车牌定位算法

车牌定位技术是车牌识别技术中最重要的部分,利用车牌图像在DCT域的水平和竖直能量值对图像进行进一步二值化处理,通过中值滤波和小区去除定位车牌.实验结果表明这种车牌定位方法具有算法实现简单、速度快、适应性强的特点.     

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。     

保税物流园区竞争性选址问题优化模型

保税物流园区的建设数量不断增加,各个园区之间的竞争问题逐渐显露,在进行新的保税物流园区建设选址时,需要考虑与现有保税物流园区的竞争问题.建立了保税物流园区竞争性选址优化模型,并针对模型设计了混合启发式算法求解.算例分析显示,货物总量一定时,随着保税物流园区建设数量的增加,每个园区货流量减少,服务质量而减少;建设规模对最大货流量产生约束,园区的服务质量不能一直增长.将程序运行10次,计算结果具有稳定性,可见算法是收敛和稳定的,模型是可行的.     

给定限期条件下应急选址问题的量子竞争决策算法

为求解给定期限条件的应急设施选址问题,本文提出了一种量子竞争决策算法.将量子个体作为博弈者参与到竞争决策中,利用量子位、叠加态等理论提高竞争群体多样性,缩小群体规模,加快优化速度;基于进化博弈论中博弈者学习和策略调整的机制,实现竞争者学习和自演化的目的,增强算法的寻优能力.实验结果表明算法的可行性和有效性.     

一类带反馈控制的非自治离散竞争系统概周期解的动力学性质

本文利用差分方程的比较原理以及构造国合适的Lyapunov函数,讨论了一类带有反馈控制的非自治离散竞争系统的持久性和概周期解,给出了存在正概周期解的几个充分条件.最后给出一个数值例子验证了本文主要结果的有效性.     

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。     

考虑顾客便利半径和质量阈值的竞争设施选址问题

在竞争设施选址问题中,顾客选择行为是决定设施占领市场份额的重要因素,其描述了需求在设施之间的分配方式。为了贴近顾客真实的光顾行为,本文提出了一种考虑顾客便利半径和质量阈值的顾客选择规则,并研究了在该规则下市场中新进入公司的竞争设施选址问题。提出了一种基于排名的遗传算法(RGA)求解该问题,并将该算法与经典遗传算法(GA)和基于排名的离散优化算法(RDOA)进行了比较,结果说明了算法的有效性以及模型中质量阈值的重要性。     

Nonadditive Shortest Paths: Subproblems in Multi-Agent Competitive Network Models

A variety of different multi-agent (competitive) network models have been described in the literature. Computational techniques for solving such models often involve the iterative solution of shortest path subproblems. Unfortunately, the most theoretically interesting models involve nonlinear cost or utility functions and they give rise to nonadditive shortest path subproblems. This paper both describes some basic existence and uniqueness results for these subproblems and develops a heuristic for solving them.     

基于离散与连续选址相结合的平面选址问题研究——以华北石油局大牛地气田污水处理厂选址为例

选址问题的研究中,大多考虑的是理论距离(例如欧式距离等);但在实际问题中,真实的公路运输距离和理论距离有较大差异,并且修建公路的成本较高.在尽量利用当前的公路交通网络同时,又能得到最优选址,在现实中具有重要意义.以华北石油局大牛地气田第一采气厂污水处理厂选址为例,分别采用重心法选址、最大值最小化选址、多目标选址等选址的方法得到污水处理厂的备选点,并结合实际距离模拟出了各个备选点的运输费用,再综合考虑当地政策和交通状况等因素,最终得到了使得运输费用最低的新的污水处理厂的位置坐标P(9.33,11.79),在该位置建立污水处理厂比之前的运输方案每年大约可节约511万元的运输费用.方法最大的优点是减小了在选址过程中理论距离与实际距离的误差,在现实中具有一定的指导意义.     

跨境水资源竞争制度模型与竞争行为

全球淡水资源稀缺与分布不平衡导致跨境水资源竞争及水安全问题日趋严峻。为了抑制过度竞争、提高流域整体效用、促进流域合作和引导生态环保行为,提出跨境水资源竞争的三种改进制度。运用制度结构图与数学模型,比较不同制度结构下流域整体效用和各国竞争行为,验证了改进制度的有效性。据此,提出我国参与跨境水资源竞争和管控的策略建议。     

Cut Generation Algorithm for the Discrete Competitive Facility Location Problem

A competitive facility location model formulated as a bilevel programming problem is considered. A new approach to the construction of estimating problems for bilevel competitive location models is proposed. An iterative algorithm for solving a series of mixed integer programming problems to obtain a pessimistic optimal solution of the model under consideration is suggested.     

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。     

离散设施选址问题研究综述

本文首先回顾了设施选址问题百年发展历史,认为其研究经历了零散研究、系统研究、不确定性研究三个阶段.离散选址问题包括中值问题、覆盖问题、中心问题、多产品问题、动态问题、多目标问题、路径选址问题、网络中心选址问题8个子问题.最后作者讨论了选址问题研究中存在的问题以及今后发展的趋势.     

Heuristic Procedures for Solving the Discrete Ordered Median Problem

We present two heuristic methods for solving the Discrete Ordered Median Problem (DOMP), for which no such approaches have been developed so far. The DOMP generalizes classical discrete facility location problems, such as the p-median and p-center. The first procedure proposed in this paper is based on a genetic algorithm developed by Moreno Vega (1996) for p-median and p-center problems. Additionally, a second heuristic approach based on the Variable Neighborhood Search metaheuristic (VNS) proposed by Hansen and Mladenović (1997) for the p-median problem is described. An extensive numerical study is presented to show the efficiency of both heuristics and compare them.     

Discrete Models of the Harmonic Oscillator and a Discrete Analogue of Gauss' Hypergeometric Equation

We consider a doubly infinite discrete-discrete version of the bispectral problem and uncover a possible discrete analog of Gauss' equation.