网络服务设施的截流—选址问题研究
摘要
设施的选址问题是在运筹学和管理科学领域普遍存在的决策问题。设施选址问题是研究如何选择设施的数目和最优位置来为用户提供相应的服务。选址决策正确与否主要取决于选址决策后能否带来经济利益、效用、个人或社会的满足以及社会价值等。本文将着重考虑服务对象为行走在日常路线上的顾客流(交通流、顾客流、信息流和水流等)的这类服务设施的选址-截流问题。本文在国内外关于网络服务设施选址布局优化理论研究现状及发展的基础上,系统地论述了作者对网络服务设施的截流-选址问题的研究成果。
第一章首先介绍选题的依据,从交通、通讯、零售和物流等方面分析了该研究的背景动机,提出本文研究的主要问题—网络设施截流-选址问题(FLPFI),最后提出本文的主要研究目标和内容。
第二章本章首先从静态确定型、动态型、随机型和竞争型四个方面对传统选址问题的研究现状进行评述。在传统选址问题的基础上,介绍了本文的研究核心问题:顾客流量产生于网络道路的服务设施截流-选址问题(FLPFI)的基本模型和研究现状。最后对本文将要应用的四种启发式算法:贪婪算法、局部搜索算法、禁忌算法和蚂蚁算法的基本原理和步骤作了详细的介绍。
第三章研究合作型FLPFI(CFLPFI)的三个扩展问题:设施带双重容量限制的CFLPFI 问题、带危险度瓶颈限制的CFLPFI 问题和和带时间约束的CFLPFI 问题。设施带双重容量限制的CFLPFI 问题是考虑了设立在网络的边上设施的满足建站最小服务量和最大服务容量的CFLPFI 问题,文中建立了该问题的混合整数规划模型,给出了基于贪婪的启发式算法。带危险度瓶颈限制的CFLPFI 问题是考虑了网络上路段的危险度的一个起点和多个讫点CFLPFI 问题。文中建立了该问题的整数规划模型,给出了计算复杂度是O ( m0 t 2 n 3)的多项式时间算法,并给出了具体算例。最后,本章研究了考虑需求流量(货物)的价格-时间函数的CFLPFI 问题,建立了该问题的混合整数规划模型,将该问题转化为传统的CFCLP 问题来解决。
第四章研究了独立型FLPFI(IFLPFI)的两个扩展问题:两种不同设施选址的mn-IFLPFI 问题和考虑设施服务半径的IFLPFI 问题。mn-IFLPFI 问题是考虑了在市场需求细分的条件下,两种提供不同服务的设施的IFLPFI 问题,文中建立了该问题的
Facility location problem is the pervasive decision problem in the field of management science. This problem is to decide to choose the optimal location strategy to serve the customers in the network. The location strategy lies on its economic profit, personal or social satisfaction and social value. This article focuses on the Facility Location Problem about Flow Interception (FLPFI), which analyze the location of facilities capturing by-passing customer flows (traffic flows, data flows and water flows etc). Therefore, this thesis presents and discusses my research and application fruit of facility location problem about flow interception based on the theory of this field.
Firstly, the article introduces the reasons of choosing this topic, analysis background and motivation from several fields such as transportation, communication, retail trade and logistics. It proposes the main problem —Facility Location Problem about Flow Interception (FLPFI), then introduces the research route and structure of the paper.
Secondly, the article summarizes the theories on traditional facility location problem, which is organized into four categories: deterministic models, dynamic models, stochastic models and competitive models. Based on traditional location problem, it introduces the basic model of FLPFI and research background. Then four heuristic algorithms: Greedy, neighborhood search, Tabu search and Ant system are presented in detail.
Thirdly, three extended Cooperative-FLPFI problem are studied. The CFLPFI with double service capacities considers the minimum capacity for guarantee profit and the maximum service capacity. The mixed-integral model and heuristic based on greedy algorithm are proposed. The CFLPFI with risk bottleneck limitation with one origin and multi-destinations is considered with objection of minimizing the total cost for setting up facilities as well as an additional security cost. This paper formulates this integral model of this problem and proposes the polynomial algorithm based on the post-order traversal substitute algorithm. The CFLPFI with travel time constraints considers the commodity price –time function. It can be tansformed to Capacitated Fixed Charge Facility Location Problem by virtual network.
Fourthly, two extended Independent-FLPFI problem are studied. The mn—IFLPFI that
is to determine the locations of type A facilities and type B facilities on the network in order that the sum of the intercepted flows are maximum. The mn-IFLPFI as a binary integer program is formulated and heuristic algorithm is presented. Then, this paper proposes the IFLPFI with service radius. Hence, a hybrid IFLPFI-MCLM with dedicated-trip demand service radius D and by-passing flow demand service radius d is proposed. A heuristic greedy algorithm as well as several variants of an ascent search and of a tabu search is developed to solve the example network. Fifthly, the stochastic FLPFI models are proposed. The FLPFI with intercepted probability we posed is a new problem to determine the minimum cost and locations of survey station on the network in order that the intercepted probability of O ? D pair is αat least. A binary integer programming formulation for this problem is constructed. Heuristic greedy algorithm and the results of computational experiments are presented. Then, the FLPFI models with uncertain demand in several scenarios are proposed, corresponding to the MAXMIN and REGRET approaches respectively. A heuristic method based on Teitz and Bart substitution algorithm is developed. Computational experiments are described and compared with the results using the branch and bound. Sixthly, we introduce the gravity model with random functions, which reflect the customers’choice behavior. It concerns four effective factors: captured market, consumptions, distance between demand and facility and facility attractiveness. This paper studies competitive models of FLPFI from three facts: regional limitation, chance limitation with random demands and linear bounded expenditures that is proportional to total utility of same path. Ant systems and greedy algorithm are developed. The experiment results given show the advantages of the above algorithm. Finally, this article concludes the main content, innovated points and presents a prospect on further studies.
第一章首先介绍选题的依据,从交通、通讯、零售和物流等方面分析了该研究的背景动机,提出本文研究的主要问题—网络设施截流-选址问题(FLPFI),最后提出本文的主要研究目标和内容。
第二章本章首先从静态确定型、动态型、随机型和竞争型四个方面对传统选址问题的研究现状进行评述。在传统选址问题的基础上,介绍了本文的研究核心问题:顾客流量产生于网络道路的服务设施截流-选址问题(FLPFI)的基本模型和研究现状。最后对本文将要应用的四种启发式算法:贪婪算法、局部搜索算法、禁忌算法和蚂蚁算法的基本原理和步骤作了详细的介绍。
第三章研究合作型FLPFI(CFLPFI)的三个扩展问题:设施带双重容量限制的CFLPFI 问题、带危险度瓶颈限制的CFLPFI 问题和和带时间约束的CFLPFI 问题。设施带双重容量限制的CFLPFI 问题是考虑了设立在网络的边上设施的满足建站最小服务量和最大服务容量的CFLPFI 问题,文中建立了该问题的混合整数规划模型,给出了基于贪婪的启发式算法。带危险度瓶颈限制的CFLPFI 问题是考虑了网络上路段的危险度的一个起点和多个讫点CFLPFI 问题。文中建立了该问题的整数规划模型,给出了计算复杂度是O ( m0 t 2 n 3)的多项式时间算法,并给出了具体算例。最后,本章研究了考虑需求流量(货物)的价格-时间函数的CFLPFI 问题,建立了该问题的混合整数规划模型,将该问题转化为传统的CFCLP 问题来解决。
第四章研究了独立型FLPFI(IFLPFI)的两个扩展问题:两种不同设施选址的mn-IFLPFI 问题和考虑设施服务半径的IFLPFI 问题。mn-IFLPFI 问题是考虑了在市场需求细分的条件下,两种提供不同服务的设施的IFLPFI 问题,文中建立了该问题的
Facility location problem is the pervasive decision problem in the field of management science. This problem is to decide to choose the optimal location strategy to serve the customers in the network. The location strategy lies on its economic profit, personal or social satisfaction and social value. This article focuses on the Facility Location Problem about Flow Interception (FLPFI), which analyze the location of facilities capturing by-passing customer flows (traffic flows, data flows and water flows etc). Therefore, this thesis presents and discusses my research and application fruit of facility location problem about flow interception based on the theory of this field.
Firstly, the article introduces the reasons of choosing this topic, analysis background and motivation from several fields such as transportation, communication, retail trade and logistics. It proposes the main problem —Facility Location Problem about Flow Interception (FLPFI), then introduces the research route and structure of the paper.
Secondly, the article summarizes the theories on traditional facility location problem, which is organized into four categories: deterministic models, dynamic models, stochastic models and competitive models. Based on traditional location problem, it introduces the basic model of FLPFI and research background. Then four heuristic algorithms: Greedy, neighborhood search, Tabu search and Ant system are presented in detail.
Thirdly, three extended Cooperative-FLPFI problem are studied. The CFLPFI with double service capacities considers the minimum capacity for guarantee profit and the maximum service capacity. The mixed-integral model and heuristic based on greedy algorithm are proposed. The CFLPFI with risk bottleneck limitation with one origin and multi-destinations is considered with objection of minimizing the total cost for setting up facilities as well as an additional security cost. This paper formulates this integral model of this problem and proposes the polynomial algorithm based on the post-order traversal substitute algorithm. The CFLPFI with travel time constraints considers the commodity price –time function. It can be tansformed to Capacitated Fixed Charge Facility Location Problem by virtual network.
Fourthly, two extended Independent-FLPFI problem are studied. The mn—IFLPFI that
is to determine the locations of type A facilities and type B facilities on the network in order that the sum of the intercepted flows are maximum. The mn-IFLPFI as a binary integer program is formulated and heuristic algorithm is presented. Then, this paper proposes the IFLPFI with service radius. Hence, a hybrid IFLPFI-MCLM with dedicated-trip demand service radius D and by-passing flow demand service radius d is proposed. A heuristic greedy algorithm as well as several variants of an ascent search and of a tabu search is developed to solve the example network. Fifthly, the stochastic FLPFI models are proposed. The FLPFI with intercepted probability we posed is a new problem to determine the minimum cost and locations of survey station on the network in order that the intercepted probability of O ? D pair is αat least. A binary integer programming formulation for this problem is constructed. Heuristic greedy algorithm and the results of computational experiments are presented. Then, the FLPFI models with uncertain demand in several scenarios are proposed, corresponding to the MAXMIN and REGRET approaches respectively. A heuristic method based on Teitz and Bart substitution algorithm is developed. Computational experiments are described and compared with the results using the branch and bound. Sixthly, we introduce the gravity model with random functions, which reflect the customers’choice behavior. It concerns four effective factors: captured market, consumptions, distance between demand and facility and facility attractiveness. This paper studies competitive models of FLPFI from three facts: regional limitation, chance limitation with random demands and linear bounded expenditures that is proportional to total utility of same path. Ant systems and greedy algorithm are developed. The experiment results given show the advantages of the above algorithm. Finally, this article concludes the main content, innovated points and presents a prospect on further studies.
引文
[1] Daskin, M. S. Network and Discrete Location: Models Algorithms and Applications. Wiley, New York, 1995
[2] 侯利红. 中国公路建设资金90% 来自民间. http: //www. snet. com. cn/newsnet/dzxw/list. asp?id=2226
[3] 段广云, 沈振宇. 高速公路交通信息发布系统实际应用中的若干问题及对策. 公路交通技术, 2004(6): 107-109
[4] 邮电统计资料汇编. 信息产业部综合规划司, 2000
[5] 覃和仁, 关琳, 谢胜利. 求解无线网络基站选址问题的一种改进遗传算法. 计算机工程与应用, 2004(15): 72-73
[6] 杨光松, 黄联芬, 肖明波. 无线移动及无线局域网高速数据业务的现状与发展. 移动通信, 2004(Z1): 115-119
[7] 易加斌. 21 世纪中国零售业的发展趋势及对策. 哈尔滨商业大学学报(社会科学版), 2004(3): 29-31
[8] 顾亚竹, 邵晓娴. 我国零售业发展之对策. 商业研究, 2005(4): 56-58
[9] 方勇. 我国零售业发展的SWOT 分析. 商业时代, 2005(6): 18-19
[10] 戢守峰. 我国零售业竞争取胜的法宝—核心竞争力分析. 商业研究, 2002(5): 1-3
[11] 蔡进. 从统计数据看我国物流发展现状. 中国储运, 2004(1): 24-27
[12] 廖海. 我国物流产业发展对策研究. 中国流通经济, 2004(9): 16-18
[13] 国家建设部: 关于加快市政公用行业市场化进程的意见, 2002
[14] Akella M. R, Batta R et al. Base Station Location and Channel Allocation in a Cellular network with Emergency Coverage Requirements. European Journal of Operation Research, 2005, 164(2): 301-323
[15] Goemans M. X, Skutella M. Cooperative Facility Location Games. Journal of Algorithms, 2004, 50(2): 194-214
[16] 周书葵, 许仕荣. 城市供水管网水质监测点优化选址的研究. 南华大学学报(理工版), 2004(3): 62-65
[17] 常玉林, 王炜. 城市紧急服务系统优化选址模型. 系统工程理论与实践, 2000(2): 104-107
[18] 方磊, 何建敏. 应急系统优化选址的模型及其算法. 系统工程学报, 2003(2): 49-54
[19] Hakimi S. L. Optimum Locations of Switching Centers and the Absolute Centers and Medians of a Graph, Operations Research, 1964, 12: 450-459
[20] Karaata M. H. On Minimizing the Cost of Location Management in Mobile Environments, Journal of Parallel and Distributed Computing, 2001, 61(6): 950-966
[21] Serra D, Ratick S, ReVelle C. The Maximum Capture Problem with Uncertainty, Environment and Planning, 1996, 23 B: 49-59
[22] Hwang H. S. A Stochastic Set-covering Location Model for both Ameliorating and Deteriorating Items. Computers and Industrial Engineering, 2004, 46(2): 313-319
[23] Wang Q, Batta R. and al. Algorithms for a Facility Location Problem with Stochastic Customer Demand and Immobile Servers. Annals of Operations Research, 2000, 111(1): 17-34
[24] Laporte G, Louveaux F. V. and al. Exact Solution to a Location Problem with Stochastic Demands. Location Science, 1995, 3(2): 134
[25] Marianov V, ReVelle C. The Queuing Probabilistic Location Set covering Problem and some Extensions. Socio-Economic Planning Science, 1994, 28(1): 167-178
[26] Berman O, Krass D, Xu C. W. Locating Flow-intercepting Facilities: New Approaches and Results. Annals of Operations Research, 1995, 60(1): 121-143
[27] Hakimi S. L. P-median Theorems for Competitive Location. Annals of Operations Research, 1986, 5(1): 79-88
[28] Drezner T, Drezner Z. Facility Location in Anticipation of Future Competition. Location Science, 1998, 6(1-4): 155-173
[29] 孙元欣, 黄培清. 竞争型连锁经营网点选址模型与遗传算法. 科学学与科学技术管理, 2001, 10: 60-63
[30] Berman O, Krass D. Flow Intercepting Spatial Interaction Model: a New Approach to Optimal Location of Competitive Facilities. Location Science, 1998, 6(1): 41-65
[31] Wu T. H, Lin J. N. Solving the Competitive Discretionary Service Facility Location Problem. European Journal of Operational Research, 2003, 144(2): 366-378
[32] Berman O, Fouska N, Larson R. C. Optimal Location of Discretionary Service Facilities. Transportation Science, 1992, 26 (3): 201-211
[33] Webber A. Ueber den Standort der Industrien. Erster Teil. Reine Theorie der Standorte. Mit einem mathematixchen Anhang von G. Pick. Tubingen, Germany: Verlag J. C. B. Mohr, 1909
[34] Weiszfeld E. Sur le Point pour Lequel la Sornme des Distances de n points Donnes est Minimum. Tohoku Mathematical Journal, 1937, 43: 355-386
[35] Hotelling H. Stability in Competition. Economic Journal, 1929, 39: 41–57
[36] Cooper L. Location-Allocation Problem. Operations Research, 1963, 11: 331-343
[37] Drezner Z, Wesolowsky G. O. A New Method for the Multifacility Minimax Location Problem. Journal of the operational research society, 1978, 24: 1507-1514
[38] Kariv O, Hakimi S. An Algorithmic Approach to Network Location Problems 2: The p-Medians. SIAM Journal on Applied Mathematics, 1979, 37: 539–560
[39] Francis R. L. On Some Problems of Rectangular Warehouse Design and Layout. The journal of Industrial Engineering, 1967, 18: 595-604
[40] Wesolowsky G.. O. Rectangular Distance Location under the Minimax Optimality Criterion. Transportation Science, 1972, 6: 103-113
[41] Chen R, Handler G. Y. A Relaxation Method for the Solution of the Minimax Location-allocation Problem in Euclidean Space. Naval Research Logistics Quarterly, 1987, 34: 775-788
[42] Masuyama S, Ibaraki T, Hasegawa T. The Computational Complexity of the m-Center Problems on the Plane. The Transactions of the Institute of Electronics and Communication Engineers of Japan, 1981, 64E: 57-64
[43] Megiddo N, Supowit K. On the Complexity of some Common Geometric Location Problems. SIAM Journal on Computing, 1984, 13: 182-196
[44] Hassin R, Levin A, Morad D. Lexicographic Local Search and the p-Center Problem. European Journal of Operational Research, 2003, 151(1): 265-279
[45] Toregas C, Swaim R and al. The Location of Emergency Service Facilities. Operation Research, 1971, 19: 1363-1373
[46] Garey M. R, Johnson D. S. Computers and Intractability: A Guide to the Theory of NP-Completeness, Freeman, New York, 1979
[47] Mattias O, Carsten P. Bo S. An Efficient Mean Field Approach to the Set Covering Problem. European Journal of Operational Research, 2001, 133 (3): 583-595
[48] Koutras M. V, Tsitmidelis S. Evaluation of Reliability Bound by Set Covering Models. Statistics and Probability Letters, 2003, 61(2): 163-175
[49] Plane D. R, Hendrick T. E. Mathematical programming and the location of fire companies for the Denver fire department. Operations Research, 1977, 25: 563-578
[50] Daskin M. S, Stern E. H. A Hierarchical Objective Set Covering Model for Emergency Medical Service Vehicle Deployment. Transportation Science, 1981, 15 (2): 137-152
[51] Church R. L, ReVelle C. The Maximal Covering Location Problem. Papers of Regional Science Association, 1974, 32: 101-118
[52] Benedict J. Three Hierarchical Objective Models which Incorporate the Concept of Excess Coverage for Locating EMS Vehicles or Hospital. M. Sc. Thesis. Northwestern University, Evanston Ⅱ, 1983
[53] Hogan K, ReVelle C. S. Conception and Applications of Backup Coverage. Management Science, 1986, 32: 1432-1444
[54] Daskin M. S. A Maximum Expected Covering Location Model: Formulation Properties and Heuristic Solution. Transportation Science, 1983, 17 (1): 48-70
[55] Berman O, Krass D, Drezner Z. The Gradual Covering Decay Location Problem on a Network. European Journal of Operational Research, 2003, 151(3): 474-480
[56] Berman O, Krass D. The Generalized Maximal Covering Location Problem. Computers and Operations Research, 2002, 29(6): 563-581
[57] Marianov V, Serra D. Location-allocation of Multiple-server Service Centers with Constrained Queues or Waiting Times. Annals of Operations Research, 2002, 111(1): 35-50
[58] Brotconrne L. Laporte G. Semet F. Ambulance Location and Relocation Models. European Journal of Operational Research, 2003, 147(4): 451-463
[59] Goldman A. J. Optimal Center Location in Simple Networks. Transportation Science, 1971, 5: 212-221
[60] Francis R. L, Cabot A. V. Properties of a Multifacility Location Problem Involving Euclidean Distance. Naval Research Logistics Quarterly, 1972(3): 335-353
[61] Francis R. L, Goldstein J. M. Location Theory: A selective bibliography. Operations Research, 1974, 22(3): 400-410
[62] ReVelle C, The Maximum Capture or Sphere of Influence Location Problem: Hotelling Revisited on a Network. Journal of Regional Science, 1986, 26 (2): 343-358
[63] Drezner Z. On the Conditional p-Median Problem. Computers and Operations Research, 1995, 22(4): 525-530
[64] Chen R. Handler G. Y. A Relaxation Method for the Solution of the Minimax Location-allocation Problem in Euclidean Space. Naval Research Logistics Quarterly, 1987, 34(8): 775-788
[65] Wesolowsky G. O. Dynamic Facility Location. Management Science, 1973, 19 (11): 1241-1248
[66] Wesolowsky G. O. Truscott W. G. The Multiperiod Location-allocation Problem with Relocation of Facilities. Management Science, 1976, 22 (1): 57-65
[67] Drezner Z. Dynamic Facility Location: The Progressive p-Median Problem. Location Science, 1995, 3 (1): 1-7
[68] Church R. L. COBRA: A New Formulation of the Class p-Median Location Problem. Annals of Operations Research, 2003, 122(1): 103-120
[69] Berman O, Drezner Z, Wesolowsky G. O. Locating Service Facilities whose Relicability is Distance. Computers and Operations Research, 2003, 30(11): 1683-1695
[70] Lorena L. A. N, Senne E. L. F. A Column Generation Approach to Capacitated p-Median Problem. Computers and Operations Research, 2004, 31(6): 863-876
[71] Cornuejols G, Fisher M, Nemhauser G. L. On the Uncapacitated Location Problem. Annals of Discrete Mathematics, 1977, 1: 163-177
[72] Swain R. A Parametric Decomposition Approach for the Solution of Uncapacitated Location Problems. Management Science, 1974, 21(2): 189-198
[73] Andreas K. A Branch and Bound Algorithm for an Uncapacitated Facility Location Problem with a Side Constraint. International Transactions in Operational Research, 1998, 5(2): 155-168
[74] Holmberg K. Exact Solution Methods for Uncapacitated Location with Convex Transportation Costs. European Journal of Operational Research, 1998, 114(1): 127-140
[75] Fernandez E, Puerto J. Multiobjective Solution of the Uncapacitated Plant Location Problem. European Journal of Operational research, 2003, 145(3): 509-529
[76] Curry G. L, Skeith R. W. A Dynamic Programming Algorithm for Facility Location and Allocation. American Institute of Industrial Engineers Transactions, 1969, 1: 133-138
[77] Geoffrion A. M, Graves G. W. Multicommodity Distribution System Design by Benders Decomposition. Management Science, 1974, 20(7): 822-844
[78] Geoffrion A. M, McBride R. Lagrangean Relaxation Applied to Capacitated Facility Location Problems. American Institute of Industrial Engineers Transactions, 1978, 10(1): 40-47
[79] Hinojosa Y, Puerto J, Fernandez F. R. A Multiperiod Two-echelon Multicommodity Capacitated Plant Location Problem. European Journal of Operation Research, 2000, 123(1): 45-65
[80] Marianov V, Serra D. Hierarchical Location-allocation Models for Congested Systems. European Journal of Operational Research, 2001, 135(1): 195-208
[81] Melkote S, Daskin M. S. Capacitated Facility Location/Network Design Problems. European Journal of Operational Research, 2001, 129(3): 481-495
[82] O’Kelly M. E. The Location of Interacting Hub Facilities. Transportation Science, 1986, 20(1): 92-106
[83] O’Kelly M. E. Activity Levels at Hub Facilities in Interacting Networks. Geographical Analysis, 1986, 18(2): 343-356
[84] Kara B. Y, Tansel B. C. On the Single-assignment p-Hub Center Problem. European Journal of Operation Research, 2000, 125(3): 648-655
[85] Alfredo M. Formulating and Solving Splittable Capacitated Multiple Allocation Hub Location Problems. Computers and Operations Research, 2005, 32(12): 3093-3109
[86] Marianov V. Location of Hubs in a Competitive Environment. European Journal of Operational Research, 1998, 114(2): 363-371
[87] Martin C. J, Roman C. Analyzing Competition for Hub Location in Intercontinental Aviation Markets. Transportation Research, 2004, 40E (1): 135-150
[88] Manne A. S. Capacity Expansion and Probabilistic Growth. Econometrica, 1961, 29 (4): 632-649
[89] Ballou R. H. Dynamic Warehouse Location Analysis. Journal of Marketing Research, 1968, 5(2): 271-276
[90] Scott A. J. Dynamic Location-allocation Systems: Some Basic Planning Strategies. Environment and Planning, 1971(3): 373-382
[91] Canel C, Khumawala B. M and al. An Algorithm for the Capacitated, Multi-commodity Multi-period Facility Location Problem. Computers and Operations Research, 2001, 28(5): 411-427
[92] Tapiero C. S. Transportation-location-allocation Problems over Time. Journal of Regional Science, 1971, 11 (3): 377-384
[93] VanRoy T. J, Erlenkotter D. A Dual-based Procedure for Dynamic Facility Location. Management Science, 1982, 28 (10): 1091-1105
[94] Gunawardane G. Dynamic Versions of Set Covering Type Public Facility Location Problems. European Journal of Operational Research, 1982, 10(1): 190-195
[95] Drezner Z. Dynamic Facility Location: The Progressive p-Median Problem. Location Science, 1995, 3 (1): 1-7
[96] Carbone R. Public Facilities under Stochastic Demand. INFOR, 1974, 12(3): 261-270
[97] Mirchandani P. B, Odoni, A. R. Locations of Medians on Stochastic Networks. Transportation Science, 1979, 13 (2): 85-97
[98] Berman O, Odoni A. R. Locating Mobile Facilities on a Network with Markovian Properties. Networks, 1982, 12: 73-86
[99] Berman O, LeBlanc. Location-relocation of Mobile Facilities on a Stochastic Network. Transportation Science, 1984, 18 (4): 315-330
[100] Mirchandani P. B. Locational Decisions on Stochastic Networks. Geographical Analysis, 1980, 12 (2): 172-183
[101] Daskin M. S, Hogan K, ReVelle C. Integration of Multiple Excess Backup and Expected Covering Models. Environment and Planning, 1988, 15 B: 15-35
[102] Berman O, Krass D. Facility Location with Stochastic Demand and Congestion. In Drezner Z, Hamacher H. W. (eds), Facility Location: Applications and Theory, Berlin, Springer, 2001
[103] Berman O, Wang J. and al. A Probability Minimax Location Problem on the Plane. Annals of Operations Research, 2003, 122: 59-70
[104] Vanston J. H, Frisbie W. P. and al. Alternate Scenario Planning. Technological Forecasting and Social Change, 1977, 10: 159-180
[105] Averbakh I. Minmax Regret Solution for Minimax Optimization Problem with Uncertainty. Operation Research Letters, 2000, 27(2): 57-65
[106] Serra D, Ratick S, ReVelle C. The Maximum Capture Problem with Uncertainty. Environment and Planning, 1996, 23 B: 49-59
[107] Serra D, Marianov V. The p-Median Problem in a Changing Network: The Case of Barcelona. Location Science, 1998, 6(1-4): 363-394
[108] Hotelling H. Stability in competition. Economic Journal, 1929, 39: 41–57
[109] 沃尔特·克里斯泰勒. 德国南部中心地原理. 北京: 商务印书馆, 1998
[110] Hanson S. Spatial Diversification and Multipurpose Travel: Implications for Choice Theory. Geographical Analysis, 1980, 22: 245-257
[111] O’Kelly M. E. A Model of the Demand of Retail Facilities, Incorporating Multistop, Multipurpose Trips. Geographical Analysis, 1981, 13: 134-148
[112] Ghosh A, McLafferty, Sara L. A Model of Consumer Propensity for Multipurpose Travel. Geographical Analysis, 1984, 16: 244-249
[113] Huff D. L. Defining and Estimating a Trading Area. Journal of Marketing, 1964, 28: 34-38
[114] Popkowski L, Peter T. L. and al. Consumer Store Choice Dynamic: An Analysis of the Competitive Market Structure for Grocery Stores. Journal of Retailing, 2000, 76(3): 323-345
[115] ReVelle C. The Maximum Capture or Sphere of Influence Location Problem: Hotelling Revisited on a Network. Journal of Regional Science, 1986, 26(2): 343-358
[116] Serra D, Marianov V, ReVelle C. The Hierarchical Maximum Capture Problem. European Journal of Operational Research, 1992, 62(3): 34–56
[117] Reilly W. J. The Law of Retail Gravitation. Knickerbocker Press, New York, 1929
[118] Nakanishi M, Cooper L. G. Parameter Estimates for Multiplicative Competitive Interaction Models Least Square Approach. Journal of Marketing Research, 1974, 11: 201-311
[119] Eiselt H. A, Laporte G.. The Maximum Capture Problem in a Weighted Network. Journal of Regional Science, 1989, 29(3): 433–439
[120] Drezner T. Locating a Single New Facility among Existing Unequally Attractive Facilities. Journal of Regional Science, 1994, 34 (2): 237-252
[121] Drezner T, Drezner Z, Eiselt H. A. Consistent and Inconsistent Rules in Competitive Facility Choice. Journal of the Operational Research Society, 1996, 47: 1494-1503
[122] Drezner T, Drezner Z, Salhi S. Solving the Multiple Competitive Facilities Location Problem. European Journal of Operational research, 2002, 142(1): 138-151
[123] Benati S. An Improved Branch & Bound Method for the Uncapacitated Competitive Location Problem. Annals of Operations Research, 2003, 122(1): 43-58
[124] Sasaki M, Fukushima M. Stackelberg Hub Location Problem. Journal of the Operations Research Society, 2001, 44(4): 390-401
[125] Shiode S, Drezner Z. A Competitive Facility Location Problem on a Tree Network with Stochastic Weights. European Journal of Operation Research, 2003, 149: 47-52
[126] Hodgson M. J. A Flow-Capturing Location -Allocation Model. Geographical Analysis, 1990, 22 (3): 270-279
[127] Sheffi Y. Urban Transportation Network. Prentice Hall, 1985
[128] Hodgson M. J, Rosing K. E, Storrier G. Applying the Flow-capturing Location-allocation Model to an Authentic Network: Edmonton, Canada. European Journal of Operational Research, 1996, 90(3): 427-443
[129] Berman O, Bertsimas D, Larson R. C. 1995. Locating Discretionary Service Facility II: Minimizing Inconvenience. Operations Research, 1995, 43 (4): 623-632
[130] Averbakh I, Berman O. Location Flow-capturing Units on a Network with Multi-counting and Diminishing Returns to Scale. European Journal of Operational Research, 1996, 91(4): 495-506
[131] Berman O, Krass D, Xu C. W. Locating Flow-intercepting Facilities: New Approaches and Results. Annals of Operations research. 1995, 60(1): 121-143
[132] Hodgson M. J, Rosing K. E. A Network Location-allocation Model Trading off Flow Capturing and p-Median Objectives. Annals of Operations Research, 1992, 40(2): 247-260
[133] Berman O, Krass D. Flow Intercepting Spatial Interaction Model: a New Approach to Optimal Location of Competitive Facilities. Location Science, 1998, 6(1): 41-65
[134] Mirchandani P. B, Rebello R, Agnetis A. The Inspection Station Location Problem in Hazardous Materials Transportation: Some Heuristics and Bound. INFOR, 1995, 33: 100-113
[135] Gendreau M, Laporte G, Parent I. Heuristic for the Location of Inspection Stations on a Network. Naval Research Logistics, 2000, 47: 287-303
[136] Lam W. H. K, Yim K. N. Evaluation of Count Location Selection Methods for O-D Matrices from Traffic Counts. Journal of Transportation Engineering, 1998, 124(4): 376-383
[137] Bianco L, Confessore G., Reverberi P. A Network Based Model for Traffic Sensor Location with Implications on O-D Matrix Estimates. Transportation science, 2001, 35: 50-60
[138] Yang H, Yang C. An Algorithm for Optimal Selection of Cordon-screen Lines in Road Network. to appear in Computer & OR, 2001
[139] Sviridenko M. I. Worse-case Analysis of the Greedy Algorithm for a Generalization of Maximum p-facility Location Problem. Operation Research Letters, 2000, 26(4): 193-197
[140] Bollapragada R, Camm J. and al. A Two-phase Greedy Algorithm to Locate and Allocation Hubs for Fixed-wireless Broadband Access. Operation Research Letters, 2005, 33(2): 134-142
[141] Maranzana F. E. On the Location o f Supply Points to Minimize Transport Costs. Operational Research Quarterly, 1964, 15: 261-270
[142] Ahuja R. K, Ergun O. and al. A Survey of Very Large-scale Neighborhood Search Techniques. Discrete Applied Mathematics, 2002, 123(1-3): 75-102
[143] Ghosh D. Neighborhood Search Heuristic for the Uncapacitated Facility Location Problem. European Journal of Operational Research, 2003, 150(1): 150-162
[144] Teitz M. B, Bart P. Heuristic Methods for Estimating the Generalized Vertex Median of a Weighted Graph, Operations Research, 1968, 16: 955-961
[145] Van L. P, Aarts E, Lenstra J. Job Shop Scheduling by Simulated Annealing. Operations Research, 1992, 40: 113-125
[146] Glover F. Tabu Search Part I. ORSA Journal on Computing, 1989, 1: 190 -206
[147] Glover F. Tabu Search Part II. ORSA Journal on Computing, 1990, 2: 4-32
[148] Glover F, Laguna M. Tabu Search. Kluwer Academic Publishers, Boston, MA, 1997
[149] Salhi S. Defining Tabu List Size and Aspiration Criterion within Tabu Search Methods. Computers and Operations Research, 2002, 29(1): 67-86
[150] Swarnkar R, Tiwari M. K. Modelling Machine Loading Problem of FMSs and its Solution Methodology Using a Hybrid Tabu Search and Simulated Annealing-based Heuristic Approach. Robotics and Computer-Integrated Manufacturing, 2004, 20(3): 199-209
[151] Aoyama I, Sato H, Nakajima K. Genetic Algorithm and Tabu Search Method for Care Service Scheduling Problem and Comparison between these two Methods. Journal of the Operations Research Society of Japan, 2001, 44(3): 280
[152] Skorin-Kapov D, Skorin-Kapov J. On Tabu Search for the Location of Interacting Hub Facilities. Location Science, 1995, 3(1): 61
[153] Tuzun D, Burke L. I. A Two-phase Tabu Search Approach to the Location Routing Problem. European Journal of Operational Research, 1999, 116(1): 87-99
[154] Gendron B, Potvin J, Soriano P. A Parallel Hybrid Heuristic for the Multicommodity Capacitatied Location Problem with Balancing Requirements. Parallel Computing, 2003, 29(5): 591-606
[155] Michel L, Van H, Pascal. A Simple Tabu Search for Warehouse Location. European Journal of Operational Research, 2004, 157(3): 576-5
[156] Dorigo M, Maniezzo V, Colomi A. The Ant System: Optimization by a Colony of Cooperating Agents. IEEE Transactions on Systems, Man, and Cybernetics, 1996, 26B(1): 29-41
[157] Dorigo M, Gambardella M. Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem. IEEE Transactions on Evolutionary Computations, 1997, 1(1): 53-66
[158] Stüzle T. Max-Min Ant System for the Quadratic Assignment Problem. Technical Report AIDA-97-4, FG Intellektik, TU Darmstadt, Germany, 1997
[159] Stüzle, T. An Ant Approach for the Flow Shop Problem. In Proceedings of the 6th European Congress on Intelligent Techniques & Soft Computing, 1998, 3: 1560–1564
[160] Bullnheimer B, Hartl R. F, Strauss C. A New Rank Based Version of the Ant System-A Computational Study. Central European Journal for Operations Research and Economics, 1998
[161] Gambardella L. M, Taillard E. D, Dorigo M. Ant Colonies for the QAP. Journal of the Operational Research Society, 1999, 50(2): 167-176
[162] Costa D, Hertz A. Ants can Color Graphs. Journal of the Operational Research Society, 1997, 48(3): 295-305
[163] 胡小兵, 黄席樾. 蚁群优化算法及其应用. 计算机仿真, 2004, 21(5): 81-85
[164] 林国辉, 马正新等. 基于蚂蚁算法的拥塞规避路由算法. 清华大学学报(自然科学版), 2003, 43(1): 37-43
[165] 马良, 项培军. 蚂蚁算法在组合优化中的应用. 管理科学学报, 2001, 4(2): 32-37
[166] Colome R, Lourenco H. R, Serra D. A New Chance-Constrained Maximum Capture Location Problem. Annals of Operations Research, 2003, 122(1): 121-139
[167] Colorni A, Dorigo M. and al. Heuristic form Nature for Hard Combinatorial Optimization Problem. International Transactions in Operational Research, 1996, 3(1): 1-21
[168] ALP O, Erkut E, Drezner Z. An Efficient Genetic Algorithm for the p-Median Problem. Annals of Operations Research, 2003, 122(1): 21-42
[169] 吴兆麟. 海上交通工程. 大连: 大连海事大学出版社, 1993
[170] 吴兆麟, 郑中义. 时间碰撞危险度及模型. 大连海事大学学报, 2001, 27(2): 1-5
[171] Huff D. L. Defining and Estimating a Trading Area. Journal of Marketing, 1964, 28: 34–38
[172] Drezner T, Marcoulides G, Drezner D. A Procedure for Estimating the Attractiveness of Shopping Malls. In Proceedings of 29th Annual DSI Meeting, 1998, 2: 1090-1092
[173] Drezner T, Drezner D. Validating the Gravity-Based Competitive Location Model Using Inferred Attractiveness. Annals of Operations Research, 2002, 111(2): 227-237
[174] Huff D. L. A Programmed Solution for Approximating an Optimum Retail Location. Land Economics, 1966, 42: 293-303
[175] Drezner T, Drezner Z. Facility Location in Anticipation of Future Competition. Location Science, 1998, 6(1-4): 155-173
[176] Bell D. R, Ho T. H, Tang C. S. Determining where to Shop: Fixed and Variable Costs of Shopping. Journal of Marketing Research, 1998, 35(3): 352-370
[177] Revelle C, Elzinga D. An Algorithm for Facility Location in a Districted Region. Environment and Planning, 1989, 16B(1): 41-50
[178] Berman O, Einav D, Handler G. The Zone-Constrained Location Problem on a Network. European Journal of Operational Research, 1991, 53(1): 14-24
[179] Jobson J. D. Applied Multivariate Data Analysis 1: Regression and Experimental Design. Springer, New York, 1991
[180] Nemhauser G. L. Wolsey L. A, Fisher M. L. Integer and Combinatorial Optimization. Wiley, New York, 1988
[2] 侯利红. 中国公路建设资金90% 来自民间. http: //www. snet. com. cn/newsnet/dzxw/list. asp?id=2226
[3] 段广云, 沈振宇. 高速公路交通信息发布系统实际应用中的若干问题及对策. 公路交通技术, 2004(6): 107-109
[4] 邮电统计资料汇编. 信息产业部综合规划司, 2000
[5] 覃和仁, 关琳, 谢胜利. 求解无线网络基站选址问题的一种改进遗传算法. 计算机工程与应用, 2004(15): 72-73
[6] 杨光松, 黄联芬, 肖明波. 无线移动及无线局域网高速数据业务的现状与发展. 移动通信, 2004(Z1): 115-119
[7] 易加斌. 21 世纪中国零售业的发展趋势及对策. 哈尔滨商业大学学报(社会科学版), 2004(3): 29-31
[8] 顾亚竹, 邵晓娴. 我国零售业发展之对策. 商业研究, 2005(4): 56-58
[9] 方勇. 我国零售业发展的SWOT 分析. 商业时代, 2005(6): 18-19
[10] 戢守峰. 我国零售业竞争取胜的法宝—核心竞争力分析. 商业研究, 2002(5): 1-3
[11] 蔡进. 从统计数据看我国物流发展现状. 中国储运, 2004(1): 24-27
[12] 廖海. 我国物流产业发展对策研究. 中国流通经济, 2004(9): 16-18
[13] 国家建设部: 关于加快市政公用行业市场化进程的意见, 2002
[14] Akella M. R, Batta R et al. Base Station Location and Channel Allocation in a Cellular network with Emergency Coverage Requirements. European Journal of Operation Research, 2005, 164(2): 301-323
[15] Goemans M. X, Skutella M. Cooperative Facility Location Games. Journal of Algorithms, 2004, 50(2): 194-214
[16] 周书葵, 许仕荣. 城市供水管网水质监测点优化选址的研究. 南华大学学报(理工版), 2004(3): 62-65
[17] 常玉林, 王炜. 城市紧急服务系统优化选址模型. 系统工程理论与实践, 2000(2): 104-107
[18] 方磊, 何建敏. 应急系统优化选址的模型及其算法. 系统工程学报, 2003(2): 49-54
[19] Hakimi S. L. Optimum Locations of Switching Centers and the Absolute Centers and Medians of a Graph, Operations Research, 1964, 12: 450-459
[20] Karaata M. H. On Minimizing the Cost of Location Management in Mobile Environments, Journal of Parallel and Distributed Computing, 2001, 61(6): 950-966
[21] Serra D, Ratick S, ReVelle C. The Maximum Capture Problem with Uncertainty, Environment and Planning, 1996, 23 B: 49-59
[22] Hwang H. S. A Stochastic Set-covering Location Model for both Ameliorating and Deteriorating Items. Computers and Industrial Engineering, 2004, 46(2): 313-319
[23] Wang Q, Batta R. and al. Algorithms for a Facility Location Problem with Stochastic Customer Demand and Immobile Servers. Annals of Operations Research, 2000, 111(1): 17-34
[24] Laporte G, Louveaux F. V. and al. Exact Solution to a Location Problem with Stochastic Demands. Location Science, 1995, 3(2): 134
[25] Marianov V, ReVelle C. The Queuing Probabilistic Location Set covering Problem and some Extensions. Socio-Economic Planning Science, 1994, 28(1): 167-178
[26] Berman O, Krass D, Xu C. W. Locating Flow-intercepting Facilities: New Approaches and Results. Annals of Operations Research, 1995, 60(1): 121-143
[27] Hakimi S. L. P-median Theorems for Competitive Location. Annals of Operations Research, 1986, 5(1): 79-88
[28] Drezner T, Drezner Z. Facility Location in Anticipation of Future Competition. Location Science, 1998, 6(1-4): 155-173
[29] 孙元欣, 黄培清. 竞争型连锁经营网点选址模型与遗传算法. 科学学与科学技术管理, 2001, 10: 60-63
[30] Berman O, Krass D. Flow Intercepting Spatial Interaction Model: a New Approach to Optimal Location of Competitive Facilities. Location Science, 1998, 6(1): 41-65
[31] Wu T. H, Lin J. N. Solving the Competitive Discretionary Service Facility Location Problem. European Journal of Operational Research, 2003, 144(2): 366-378
[32] Berman O, Fouska N, Larson R. C. Optimal Location of Discretionary Service Facilities. Transportation Science, 1992, 26 (3): 201-211
[33] Webber A. Ueber den Standort der Industrien. Erster Teil. Reine Theorie der Standorte. Mit einem mathematixchen Anhang von G. Pick. Tubingen, Germany: Verlag J. C. B. Mohr, 1909
[34] Weiszfeld E. Sur le Point pour Lequel la Sornme des Distances de n points Donnes est Minimum. Tohoku Mathematical Journal, 1937, 43: 355-386
[35] Hotelling H. Stability in Competition. Economic Journal, 1929, 39: 41–57
[36] Cooper L. Location-Allocation Problem. Operations Research, 1963, 11: 331-343
[37] Drezner Z, Wesolowsky G. O. A New Method for the Multifacility Minimax Location Problem. Journal of the operational research society, 1978, 24: 1507-1514
[38] Kariv O, Hakimi S. An Algorithmic Approach to Network Location Problems 2: The p-Medians. SIAM Journal on Applied Mathematics, 1979, 37: 539–560
[39] Francis R. L. On Some Problems of Rectangular Warehouse Design and Layout. The journal of Industrial Engineering, 1967, 18: 595-604
[40] Wesolowsky G.. O. Rectangular Distance Location under the Minimax Optimality Criterion. Transportation Science, 1972, 6: 103-113
[41] Chen R, Handler G. Y. A Relaxation Method for the Solution of the Minimax Location-allocation Problem in Euclidean Space. Naval Research Logistics Quarterly, 1987, 34: 775-788
[42] Masuyama S, Ibaraki T, Hasegawa T. The Computational Complexity of the m-Center Problems on the Plane. The Transactions of the Institute of Electronics and Communication Engineers of Japan, 1981, 64E: 57-64
[43] Megiddo N, Supowit K. On the Complexity of some Common Geometric Location Problems. SIAM Journal on Computing, 1984, 13: 182-196
[44] Hassin R, Levin A, Morad D. Lexicographic Local Search and the p-Center Problem. European Journal of Operational Research, 2003, 151(1): 265-279
[45] Toregas C, Swaim R and al. The Location of Emergency Service Facilities. Operation Research, 1971, 19: 1363-1373
[46] Garey M. R, Johnson D. S. Computers and Intractability: A Guide to the Theory of NP-Completeness, Freeman, New York, 1979
[47] Mattias O, Carsten P. Bo S. An Efficient Mean Field Approach to the Set Covering Problem. European Journal of Operational Research, 2001, 133 (3): 583-595
[48] Koutras M. V, Tsitmidelis S. Evaluation of Reliability Bound by Set Covering Models. Statistics and Probability Letters, 2003, 61(2): 163-175
[49] Plane D. R, Hendrick T. E. Mathematical programming and the location of fire companies for the Denver fire department. Operations Research, 1977, 25: 563-578
[50] Daskin M. S, Stern E. H. A Hierarchical Objective Set Covering Model for Emergency Medical Service Vehicle Deployment. Transportation Science, 1981, 15 (2): 137-152
[51] Church R. L, ReVelle C. The Maximal Covering Location Problem. Papers of Regional Science Association, 1974, 32: 101-118
[52] Benedict J. Three Hierarchical Objective Models which Incorporate the Concept of Excess Coverage for Locating EMS Vehicles or Hospital. M. Sc. Thesis. Northwestern University, Evanston Ⅱ, 1983
[53] Hogan K, ReVelle C. S. Conception and Applications of Backup Coverage. Management Science, 1986, 32: 1432-1444
[54] Daskin M. S. A Maximum Expected Covering Location Model: Formulation Properties and Heuristic Solution. Transportation Science, 1983, 17 (1): 48-70
[55] Berman O, Krass D, Drezner Z. The Gradual Covering Decay Location Problem on a Network. European Journal of Operational Research, 2003, 151(3): 474-480
[56] Berman O, Krass D. The Generalized Maximal Covering Location Problem. Computers and Operations Research, 2002, 29(6): 563-581
[57] Marianov V, Serra D. Location-allocation of Multiple-server Service Centers with Constrained Queues or Waiting Times. Annals of Operations Research, 2002, 111(1): 35-50
[58] Brotconrne L. Laporte G. Semet F. Ambulance Location and Relocation Models. European Journal of Operational Research, 2003, 147(4): 451-463
[59] Goldman A. J. Optimal Center Location in Simple Networks. Transportation Science, 1971, 5: 212-221
[60] Francis R. L, Cabot A. V. Properties of a Multifacility Location Problem Involving Euclidean Distance. Naval Research Logistics Quarterly, 1972(3): 335-353
[61] Francis R. L, Goldstein J. M. Location Theory: A selective bibliography. Operations Research, 1974, 22(3): 400-410
[62] ReVelle C, The Maximum Capture or Sphere of Influence Location Problem: Hotelling Revisited on a Network. Journal of Regional Science, 1986, 26 (2): 343-358
[63] Drezner Z. On the Conditional p-Median Problem. Computers and Operations Research, 1995, 22(4): 525-530
[64] Chen R. Handler G. Y. A Relaxation Method for the Solution of the Minimax Location-allocation Problem in Euclidean Space. Naval Research Logistics Quarterly, 1987, 34(8): 775-788
[65] Wesolowsky G. O. Dynamic Facility Location. Management Science, 1973, 19 (11): 1241-1248
[66] Wesolowsky G. O. Truscott W. G. The Multiperiod Location-allocation Problem with Relocation of Facilities. Management Science, 1976, 22 (1): 57-65
[67] Drezner Z. Dynamic Facility Location: The Progressive p-Median Problem. Location Science, 1995, 3 (1): 1-7
[68] Church R. L. COBRA: A New Formulation of the Class p-Median Location Problem. Annals of Operations Research, 2003, 122(1): 103-120
[69] Berman O, Drezner Z, Wesolowsky G. O. Locating Service Facilities whose Relicability is Distance. Computers and Operations Research, 2003, 30(11): 1683-1695
[70] Lorena L. A. N, Senne E. L. F. A Column Generation Approach to Capacitated p-Median Problem. Computers and Operations Research, 2004, 31(6): 863-876
[71] Cornuejols G, Fisher M, Nemhauser G. L. On the Uncapacitated Location Problem. Annals of Discrete Mathematics, 1977, 1: 163-177
[72] Swain R. A Parametric Decomposition Approach for the Solution of Uncapacitated Location Problems. Management Science, 1974, 21(2): 189-198
[73] Andreas K. A Branch and Bound Algorithm for an Uncapacitated Facility Location Problem with a Side Constraint. International Transactions in Operational Research, 1998, 5(2): 155-168
[74] Holmberg K. Exact Solution Methods for Uncapacitated Location with Convex Transportation Costs. European Journal of Operational Research, 1998, 114(1): 127-140
[75] Fernandez E, Puerto J. Multiobjective Solution of the Uncapacitated Plant Location Problem. European Journal of Operational research, 2003, 145(3): 509-529
[76] Curry G. L, Skeith R. W. A Dynamic Programming Algorithm for Facility Location and Allocation. American Institute of Industrial Engineers Transactions, 1969, 1: 133-138
[77] Geoffrion A. M, Graves G. W. Multicommodity Distribution System Design by Benders Decomposition. Management Science, 1974, 20(7): 822-844
[78] Geoffrion A. M, McBride R. Lagrangean Relaxation Applied to Capacitated Facility Location Problems. American Institute of Industrial Engineers Transactions, 1978, 10(1): 40-47
[79] Hinojosa Y, Puerto J, Fernandez F. R. A Multiperiod Two-echelon Multicommodity Capacitated Plant Location Problem. European Journal of Operation Research, 2000, 123(1): 45-65
[80] Marianov V, Serra D. Hierarchical Location-allocation Models for Congested Systems. European Journal of Operational Research, 2001, 135(1): 195-208
[81] Melkote S, Daskin M. S. Capacitated Facility Location/Network Design Problems. European Journal of Operational Research, 2001, 129(3): 481-495
[82] O’Kelly M. E. The Location of Interacting Hub Facilities. Transportation Science, 1986, 20(1): 92-106
[83] O’Kelly M. E. Activity Levels at Hub Facilities in Interacting Networks. Geographical Analysis, 1986, 18(2): 343-356
[84] Kara B. Y, Tansel B. C. On the Single-assignment p-Hub Center Problem. European Journal of Operation Research, 2000, 125(3): 648-655
[85] Alfredo M. Formulating and Solving Splittable Capacitated Multiple Allocation Hub Location Problems. Computers and Operations Research, 2005, 32(12): 3093-3109
[86] Marianov V. Location of Hubs in a Competitive Environment. European Journal of Operational Research, 1998, 114(2): 363-371
[87] Martin C. J, Roman C. Analyzing Competition for Hub Location in Intercontinental Aviation Markets. Transportation Research, 2004, 40E (1): 135-150
[88] Manne A. S. Capacity Expansion and Probabilistic Growth. Econometrica, 1961, 29 (4): 632-649
[89] Ballou R. H. Dynamic Warehouse Location Analysis. Journal of Marketing Research, 1968, 5(2): 271-276
[90] Scott A. J. Dynamic Location-allocation Systems: Some Basic Planning Strategies. Environment and Planning, 1971(3): 373-382
[91] Canel C, Khumawala B. M and al. An Algorithm for the Capacitated, Multi-commodity Multi-period Facility Location Problem. Computers and Operations Research, 2001, 28(5): 411-427
[92] Tapiero C. S. Transportation-location-allocation Problems over Time. Journal of Regional Science, 1971, 11 (3): 377-384
[93] VanRoy T. J, Erlenkotter D. A Dual-based Procedure for Dynamic Facility Location. Management Science, 1982, 28 (10): 1091-1105
[94] Gunawardane G. Dynamic Versions of Set Covering Type Public Facility Location Problems. European Journal of Operational Research, 1982, 10(1): 190-195
[95] Drezner Z. Dynamic Facility Location: The Progressive p-Median Problem. Location Science, 1995, 3 (1): 1-7
[96] Carbone R. Public Facilities under Stochastic Demand. INFOR, 1974, 12(3): 261-270
[97] Mirchandani P. B, Odoni, A. R. Locations of Medians on Stochastic Networks. Transportation Science, 1979, 13 (2): 85-97
[98] Berman O, Odoni A. R. Locating Mobile Facilities on a Network with Markovian Properties. Networks, 1982, 12: 73-86
[99] Berman O, LeBlanc. Location-relocation of Mobile Facilities on a Stochastic Network. Transportation Science, 1984, 18 (4): 315-330
[100] Mirchandani P. B. Locational Decisions on Stochastic Networks. Geographical Analysis, 1980, 12 (2): 172-183
[101] Daskin M. S, Hogan K, ReVelle C. Integration of Multiple Excess Backup and Expected Covering Models. Environment and Planning, 1988, 15 B: 15-35
[102] Berman O, Krass D. Facility Location with Stochastic Demand and Congestion. In Drezner Z, Hamacher H. W. (eds), Facility Location: Applications and Theory, Berlin, Springer, 2001
[103] Berman O, Wang J. and al. A Probability Minimax Location Problem on the Plane. Annals of Operations Research, 2003, 122: 59-70
[104] Vanston J. H, Frisbie W. P. and al. Alternate Scenario Planning. Technological Forecasting and Social Change, 1977, 10: 159-180
[105] Averbakh I. Minmax Regret Solution for Minimax Optimization Problem with Uncertainty. Operation Research Letters, 2000, 27(2): 57-65
[106] Serra D, Ratick S, ReVelle C. The Maximum Capture Problem with Uncertainty. Environment and Planning, 1996, 23 B: 49-59
[107] Serra D, Marianov V. The p-Median Problem in a Changing Network: The Case of Barcelona. Location Science, 1998, 6(1-4): 363-394
[108] Hotelling H. Stability in competition. Economic Journal, 1929, 39: 41–57
[109] 沃尔特·克里斯泰勒. 德国南部中心地原理. 北京: 商务印书馆, 1998
[110] Hanson S. Spatial Diversification and Multipurpose Travel: Implications for Choice Theory. Geographical Analysis, 1980, 22: 245-257
[111] O’Kelly M. E. A Model of the Demand of Retail Facilities, Incorporating Multistop, Multipurpose Trips. Geographical Analysis, 1981, 13: 134-148
[112] Ghosh A, McLafferty, Sara L. A Model of Consumer Propensity for Multipurpose Travel. Geographical Analysis, 1984, 16: 244-249
[113] Huff D. L. Defining and Estimating a Trading Area. Journal of Marketing, 1964, 28: 34-38
[114] Popkowski L, Peter T. L. and al. Consumer Store Choice Dynamic: An Analysis of the Competitive Market Structure for Grocery Stores. Journal of Retailing, 2000, 76(3): 323-345
[115] ReVelle C. The Maximum Capture or Sphere of Influence Location Problem: Hotelling Revisited on a Network. Journal of Regional Science, 1986, 26(2): 343-358
[116] Serra D, Marianov V, ReVelle C. The Hierarchical Maximum Capture Problem. European Journal of Operational Research, 1992, 62(3): 34–56
[117] Reilly W. J. The Law of Retail Gravitation. Knickerbocker Press, New York, 1929
[118] Nakanishi M, Cooper L. G. Parameter Estimates for Multiplicative Competitive Interaction Models Least Square Approach. Journal of Marketing Research, 1974, 11: 201-311
[119] Eiselt H. A, Laporte G.. The Maximum Capture Problem in a Weighted Network. Journal of Regional Science, 1989, 29(3): 433–439
[120] Drezner T. Locating a Single New Facility among Existing Unequally Attractive Facilities. Journal of Regional Science, 1994, 34 (2): 237-252
[121] Drezner T, Drezner Z, Eiselt H. A. Consistent and Inconsistent Rules in Competitive Facility Choice. Journal of the Operational Research Society, 1996, 47: 1494-1503
[122] Drezner T, Drezner Z, Salhi S. Solving the Multiple Competitive Facilities Location Problem. European Journal of Operational research, 2002, 142(1): 138-151
[123] Benati S. An Improved Branch & Bound Method for the Uncapacitated Competitive Location Problem. Annals of Operations Research, 2003, 122(1): 43-58
[124] Sasaki M, Fukushima M. Stackelberg Hub Location Problem. Journal of the Operations Research Society, 2001, 44(4): 390-401
[125] Shiode S, Drezner Z. A Competitive Facility Location Problem on a Tree Network with Stochastic Weights. European Journal of Operation Research, 2003, 149: 47-52
[126] Hodgson M. J. A Flow-Capturing Location -Allocation Model. Geographical Analysis, 1990, 22 (3): 270-279
[127] Sheffi Y. Urban Transportation Network. Prentice Hall, 1985
[128] Hodgson M. J, Rosing K. E, Storrier G. Applying the Flow-capturing Location-allocation Model to an Authentic Network: Edmonton, Canada. European Journal of Operational Research, 1996, 90(3): 427-443
[129] Berman O, Bertsimas D, Larson R. C. 1995. Locating Discretionary Service Facility II: Minimizing Inconvenience. Operations Research, 1995, 43 (4): 623-632
[130] Averbakh I, Berman O. Location Flow-capturing Units on a Network with Multi-counting and Diminishing Returns to Scale. European Journal of Operational Research, 1996, 91(4): 495-506
[131] Berman O, Krass D, Xu C. W. Locating Flow-intercepting Facilities: New Approaches and Results. Annals of Operations research. 1995, 60(1): 121-143
[132] Hodgson M. J, Rosing K. E. A Network Location-allocation Model Trading off Flow Capturing and p-Median Objectives. Annals of Operations Research, 1992, 40(2): 247-260
[133] Berman O, Krass D. Flow Intercepting Spatial Interaction Model: a New Approach to Optimal Location of Competitive Facilities. Location Science, 1998, 6(1): 41-65
[134] Mirchandani P. B, Rebello R, Agnetis A. The Inspection Station Location Problem in Hazardous Materials Transportation: Some Heuristics and Bound. INFOR, 1995, 33: 100-113
[135] Gendreau M, Laporte G, Parent I. Heuristic for the Location of Inspection Stations on a Network. Naval Research Logistics, 2000, 47: 287-303
[136] Lam W. H. K, Yim K. N. Evaluation of Count Location Selection Methods for O-D Matrices from Traffic Counts. Journal of Transportation Engineering, 1998, 124(4): 376-383
[137] Bianco L, Confessore G., Reverberi P. A Network Based Model for Traffic Sensor Location with Implications on O-D Matrix Estimates. Transportation science, 2001, 35: 50-60
[138] Yang H, Yang C. An Algorithm for Optimal Selection of Cordon-screen Lines in Road Network. to appear in Computer & OR, 2001
[139] Sviridenko M. I. Worse-case Analysis of the Greedy Algorithm for a Generalization of Maximum p-facility Location Problem. Operation Research Letters, 2000, 26(4): 193-197
[140] Bollapragada R, Camm J. and al. A Two-phase Greedy Algorithm to Locate and Allocation Hubs for Fixed-wireless Broadband Access. Operation Research Letters, 2005, 33(2): 134-142
[141] Maranzana F. E. On the Location o f Supply Points to Minimize Transport Costs. Operational Research Quarterly, 1964, 15: 261-270
[142] Ahuja R. K, Ergun O. and al. A Survey of Very Large-scale Neighborhood Search Techniques. Discrete Applied Mathematics, 2002, 123(1-3): 75-102
[143] Ghosh D. Neighborhood Search Heuristic for the Uncapacitated Facility Location Problem. European Journal of Operational Research, 2003, 150(1): 150-162
[144] Teitz M. B, Bart P. Heuristic Methods for Estimating the Generalized Vertex Median of a Weighted Graph, Operations Research, 1968, 16: 955-961
[145] Van L. P, Aarts E, Lenstra J. Job Shop Scheduling by Simulated Annealing. Operations Research, 1992, 40: 113-125
[146] Glover F. Tabu Search Part I. ORSA Journal on Computing, 1989, 1: 190 -206
[147] Glover F. Tabu Search Part II. ORSA Journal on Computing, 1990, 2: 4-32
[148] Glover F, Laguna M. Tabu Search. Kluwer Academic Publishers, Boston, MA, 1997
[149] Salhi S. Defining Tabu List Size and Aspiration Criterion within Tabu Search Methods. Computers and Operations Research, 2002, 29(1): 67-86
[150] Swarnkar R, Tiwari M. K. Modelling Machine Loading Problem of FMSs and its Solution Methodology Using a Hybrid Tabu Search and Simulated Annealing-based Heuristic Approach. Robotics and Computer-Integrated Manufacturing, 2004, 20(3): 199-209
[151] Aoyama I, Sato H, Nakajima K. Genetic Algorithm and Tabu Search Method for Care Service Scheduling Problem and Comparison between these two Methods. Journal of the Operations Research Society of Japan, 2001, 44(3): 280
[152] Skorin-Kapov D, Skorin-Kapov J. On Tabu Search for the Location of Interacting Hub Facilities. Location Science, 1995, 3(1): 61
[153] Tuzun D, Burke L. I. A Two-phase Tabu Search Approach to the Location Routing Problem. European Journal of Operational Research, 1999, 116(1): 87-99
[154] Gendron B, Potvin J, Soriano P. A Parallel Hybrid Heuristic for the Multicommodity Capacitatied Location Problem with Balancing Requirements. Parallel Computing, 2003, 29(5): 591-606
[155] Michel L, Van H, Pascal. A Simple Tabu Search for Warehouse Location. European Journal of Operational Research, 2004, 157(3): 576-5
[156] Dorigo M, Maniezzo V, Colomi A. The Ant System: Optimization by a Colony of Cooperating Agents. IEEE Transactions on Systems, Man, and Cybernetics, 1996, 26B(1): 29-41
[157] Dorigo M, Gambardella M. Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem. IEEE Transactions on Evolutionary Computations, 1997, 1(1): 53-66
[158] Stüzle T. Max-Min Ant System for the Quadratic Assignment Problem. Technical Report AIDA-97-4, FG Intellektik, TU Darmstadt, Germany, 1997
[159] Stüzle, T. An Ant Approach for the Flow Shop Problem. In Proceedings of the 6th European Congress on Intelligent Techniques & Soft Computing, 1998, 3: 1560–1564
[160] Bullnheimer B, Hartl R. F, Strauss C. A New Rank Based Version of the Ant System-A Computational Study. Central European Journal for Operations Research and Economics, 1998
[161] Gambardella L. M, Taillard E. D, Dorigo M. Ant Colonies for the QAP. Journal of the Operational Research Society, 1999, 50(2): 167-176
[162] Costa D, Hertz A. Ants can Color Graphs. Journal of the Operational Research Society, 1997, 48(3): 295-305
[163] 胡小兵, 黄席樾. 蚁群优化算法及其应用. 计算机仿真, 2004, 21(5): 81-85
[164] 林国辉, 马正新等. 基于蚂蚁算法的拥塞规避路由算法. 清华大学学报(自然科学版), 2003, 43(1): 37-43
[165] 马良, 项培军. 蚂蚁算法在组合优化中的应用. 管理科学学报, 2001, 4(2): 32-37
[166] Colome R, Lourenco H. R, Serra D. A New Chance-Constrained Maximum Capture Location Problem. Annals of Operations Research, 2003, 122(1): 121-139
[167] Colorni A, Dorigo M. and al. Heuristic form Nature for Hard Combinatorial Optimization Problem. International Transactions in Operational Research, 1996, 3(1): 1-21
[168] ALP O, Erkut E, Drezner Z. An Efficient Genetic Algorithm for the p-Median Problem. Annals of Operations Research, 2003, 122(1): 21-42
[169] 吴兆麟. 海上交通工程. 大连: 大连海事大学出版社, 1993
[170] 吴兆麟, 郑中义. 时间碰撞危险度及模型. 大连海事大学学报, 2001, 27(2): 1-5
[171] Huff D. L. Defining and Estimating a Trading Area. Journal of Marketing, 1964, 28: 34–38
[172] Drezner T, Marcoulides G, Drezner D. A Procedure for Estimating the Attractiveness of Shopping Malls. In Proceedings of 29th Annual DSI Meeting, 1998, 2: 1090-1092
[173] Drezner T, Drezner D. Validating the Gravity-Based Competitive Location Model Using Inferred Attractiveness. Annals of Operations Research, 2002, 111(2): 227-237
[174] Huff D. L. A Programmed Solution for Approximating an Optimum Retail Location. Land Economics, 1966, 42: 293-303
[175] Drezner T, Drezner Z. Facility Location in Anticipation of Future Competition. Location Science, 1998, 6(1-4): 155-173
[176] Bell D. R, Ho T. H, Tang C. S. Determining where to Shop: Fixed and Variable Costs of Shopping. Journal of Marketing Research, 1998, 35(3): 352-370
[177] Revelle C, Elzinga D. An Algorithm for Facility Location in a Districted Region. Environment and Planning, 1989, 16B(1): 41-50
[178] Berman O, Einav D, Handler G. The Zone-Constrained Location Problem on a Network. European Journal of Operational Research, 1991, 53(1): 14-24
[179] Jobson J. D. Applied Multivariate Data Analysis 1: Regression and Experimental Design. Springer, New York, 1991
[180] Nemhauser G. L. Wolsey L. A, Fisher M. L. Integer and Combinatorial Optimization. Wiley, New York, 1988