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Location Models in Transportation

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Handbook of Transportation Science

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10.7 References

  • Aneja, Y. P. and Parlar, M. (1994) Algorithms for Weber facility location in the presence of forbidden regions and/or barriers to travel. Transportation Science 28, 70–76.

    Google Scholar 

  • Averbakh, I. (1997) On the complexity of a class of robust location problems. Working Paper, Western Washington University.

    Google Scholar 

  • Averbakh, I. and Berman, O. (1997a) Algorithms for the robust 1-center problem. Working Paper.

    Google Scholar 

  • Averbakh, I. and Berman, O. (1997b) Minimax regret p-center location on a network with demand uncertainty. Location Science 5, 247–254.

    Article  Google Scholar 

  • Averbakh, I. and Berman, O. (1997c) Minimax regret robust median location on a network under uncertainty. Working Paper.

    Google Scholar 

  • Ballou, R. H. (1968) Dynamic warehouse location analysis. Journal of Marketing Research 5, 271–276.

    Google Scholar 

  • Batta R., Dolan J. M. and Krishnamurthy, N. N. (1989) The maximal expected covering location problem: Revisited. Transportation Science 23, 277–287.

    MathSciNet  Google Scholar 

  • Batta, R., Ghose, A. and Palekar, U. S. (1989) Locating facilities on the Manhattan metric with arbitrary shaped barriers and convex forbidden regions, Transportation Science 23, 26–36.

    MathSciNet  Google Scholar 

  • Bean, J. C., Higle, J. L. and Smith, R. L. (1992) Capacity expansion under stochastic demands, Operations Research 40, S210–S216.

    Google Scholar 

  • Belardo, S., Harrald, J., Wallace, W. A. and Ward, J. (1984) A partial covering approach to siting response resources for major maritime oil spills. Management Science 30, 1184–1196.

    Google Scholar 

  • Benedict, J. M. (1983) Three hierarchical objective models which incorporate the concept of excess coverage to locate ems vehicles or hospitals. M.S. thesis, Department of Civil Engineering, Northwestern University, Evanston, 1L 60208.

    Google Scholar 

  • Berger, R. T. (1997) Location-Routing Models for Distribution System Design. Ph.D. dissertation, Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, 1L60208.

    Google Scholar 

  • Berman, O. (1985) Locating a facility on a congested network with random lengths. Networks, 15, 275–294.

    MATH  MathSciNet  Google Scholar 

  • Berman, O., Ingco, D. I. and Odoni, A. R. (1992) Improving the location of minisum facilities through network modification. Annals of Operations Research 40, 1–16.

    Article  MathSciNet  Google Scholar 

  • Berman O., Larson, R. C. and Chiu, S. S. (1985) Optimal server location on a network operating as an M/G/1 queue. Operations Research 33, 746–771.

    MathSciNet  Google Scholar 

  • Berman, O. and LeBlanc, B. (1984) Location-relocation of mobile facilities on a stochastic network. Transportation Science 18, 315–330.

    MathSciNet  Google Scholar 

  • Berman, O. and Odoni, A. R. (1982) Locating mobile servers on a network with Markovian properties. Networks 12, 73–86.

    MathSciNet  Google Scholar 

  • Bodin, L., Golden, B. L., Assad, A., and Ball M. (1983) The state of the art in the routing and scheduling of vehicles and crews. Computers and Operations Research 10, 63–212.

    MathSciNet  Google Scholar 

  • Bramel, J. and Simchi-Levi, D. (1995) A location based heuristic for general routing problems. Operations Research 43, 649–660.

    MathSciNet  Google Scholar 

  • Brandeau, M. L. and Chiu, S. S. (1989) An overview of representative problems in location research. Management Science 35, 645–674

    MathSciNet  Google Scholar 

  • Campbell, J. F. (1990) Locating transportation terminals to serve an expanding demand. Transportation Research 24B, 173–192.

    Google Scholar 

  • Campbell, J. F. (1994) Integer programming formulations of discrete hub location problems. European Journal of Operational Research 72, 387–405.

    Article  MATH  Google Scholar 

  • Carbone, R. (1974) Public facilities location under stochastic demand. 1NFOR 12, 261–270.

    MATH  MathSciNet  Google Scholar 

  • Carson, Y. M. and Batta, R. (1990) Locating an ambulance on the Amherst campus of the State University of New York at Buffalo. Interfaces 20:5, 43–49.

    Google Scholar 

  • Chapman, S. C. and White, J. A. (1974) Probabilistic formulations ofemergency service facilities location problems. Paper presented al the 1974 ORSA/T1MS Conference, San Juan, Puerto Rico.

    Google Scholar 

  • Chien, T. W., Balakrishnan, A. and Wong, R. T. (1989) An integrated inventory allocation and vehicle routing problem. Transportation Science 23, 67–76.

    MathSciNet  Google Scholar 

  • Church, R. L. and Meadows, M (1979) Location modeling utilizing maximum service distance criteria. Geographical Analysis 11, 358–373.

    Google Scholar 

  • Church, R. L. and ReVelle, C. (1974) The maximal covering location problem. Papers of the Regional Science Association 32, 101–118.

    Article  Google Scholar 

  • Clarke, G. and Wright, J. W. (1964) Scheduling of vehicles from a central depot to a number of delivery points. Operations Research 12, 568–581.

    Google Scholar 

  • Cohon, J. L. (1978) Multiobjeclive Programming and Planning. Academic Press, New York, NY.

    Google Scholar 

  • Current, J., Min, H. and Schilling, D. (1990) Multiobjective analysis of facility location decisions. European Journal of Operational Research 49, 295–307.

    Article  Google Scholar 

  • Current, J., Ratick, S. and ReVelle, C. (1997) Dynamic facility location when the total number offacilities is uncertain: A decision analysis approach. Forthcoming in the European Journal of Operational Research.

    Google Scholar 

  • Current, J., ReVelle, C. and Cohon, J. (1985) The maximum-covering/shortest-path problem: A multiobjective network design and routing problem. European Journal of Operational Research 21, 189–199.

    Article  MathSciNet  Google Scholar 

  • Current, J., ReVelle, C. and Cohon, J. (1988) The minimum-covering/shortest-path problem. Decision Sciences 19, 490–503.

    Google Scholar 

  • Daskin, M. S. (1982) Application of an expected covering model to emergency medical service system design. Decision Sciences 13, 416–439.

    Google Scholar 

  • Daskin, M. S. (1983) A maximum expected covering location model: Formulation, properties and heuristic solution. Transportation Science 17, 48–70.

    Google Scholar 

  • Daskin, M. S., Hesse, S. M. and ReVelle, C. S. (1997) α-reliable P-minimax regret: A new model for strategic facility location modeling. Location Science 5, 227–246.

    Article  Google Scholar 

  • Daskin, M. S., Hogan, K. and ReVelle, C. (1988) Integration of multiple, excess, backup, and expected covering models. Environment and Planning B 15, 15–35.

    Google Scholar 

  • Daskin, M. S., Jones, P. C. and Lowe, T. J. (1990) Rationalizing tool selection in a flexible manufacturing system for sheet metal products. Operations Research 38, 1104–1115.

    Google Scholar 

  • Daskin, M. S. and Owen, S. H. (1998) Two new location covering problems: The partial covering P-center problem and the partial set covering problem. Forthcoming in Geographical Analysis.

    Google Scholar 

  • Daskin, M. S. and Stern, E. (1981) A hierarchical objective set covering model for emergency medical service vehicle deployment, Transportation Science 15, 137–152.

    MathSciNet  Google Scholar 

  • Densham, P. J. and Rushton, G. (1992) A more efficient heuristic for solving large P-median problems. Papers in Regional Science: The Journal of the RSAI 71, 307–329.

    Google Scholar 

  • Drezner, Z. (1995) Dynamic facility location: The progressive P-median problem. Location Science 3, 1–7.

    MATH  Google Scholar 

  • Drezner, Z. and Wesolowsky, G. O. (1991) Facility location when demand is time dependent. Naval Research Logistics 38, 763–777.

    MathSciNet  Google Scholar 

  • Duhamel, C., Potvin, J. Y. and Rousseau, J. M. (1997) A tabu search heuristic for the vehicle routing problem with backhauls and time windows. Transportation Science 31, 49–59.

    Google Scholar 

  • Eaton, D. and Daskin, M. S. (1980) A multiple model approach to planning emergency medical service vehicle deployment. Proceedings of the International Conference on Systems Science in Health Care ed. C. Tilquin, pp. 951–959, Pergamon Press, Montreal, Canada.

    Google Scholar 

  • Eaton, D., Daskin, M. S., Simmons, D., Bulloch, B. and Jansma, G. (1985) Determining emergency medical service vehicle deployment in Austin, Texas. Interfaces 15:1,96–108.

    Google Scholar 

  • Eilon, S., Watson-Gandy, C. D. T. and Christofides, N. (1971) Distribution Management: Mathematical Modelling and Practical Analysis. Griffin, London.

    Google Scholar 

  • Erkut, E. and Neuman, S. (1989) Analytical models for locating undesirable facilities. European Journal of Operational Research 40, 275–291.

    Article  MathSciNet  Google Scholar 

  • Erkut, E. and Neuman, S. (1992) A multiobjective model for locating undesirable facilities. Annals of Operational Research 40, 209–227.

    Google Scholar 

  • Erkut, E. and Verter, V. (1995) Hazardous materials logistics. Facility Location: A Survey of Applications and Methods ed. Z. Drezner, pp. 467–506, Springer-Verlag, New York.

    Google Scholar 

  • Erlenkotter, D. (1978) A dual-based procedure for uncapacitated facility location. Operations Research 26, 992–1009.

    MATH  MathSciNet  Google Scholar 

  • Ernst, A. T. and Krishnamoorthy, M. (1996) Efficient algorithms for the uncapacitated single allocation p-hub median problem. Location Science 4, 139–154.

    Article  Google Scholar 

  • Fisher, M. L. (1981) The Lagrangian relaxation method for solving integer programming problems. Management Science 27, 1–18.

    MATH  MathSciNet  Google Scholar 

  • Fisher, M. L. (1985) An applications oriented guide to Lagrangian relaxation. Interfaces 15:2, 10–21.

    Google Scholar 

  • Fisher, M. L. (1995) Vehicle routing. Handbooks in Operations Research and Management Science: Network Routing eds M. O. Ball, T. L. Magnanti, C. L. Monma and G. L. Nemhauser, pp. 1–33. Elsevier Science Publishers, North Holland, Amsterdam.

    Google Scholar 

  • Fisher, M. L, and Jaikumar, R. (1981) A generalized assignment heuristic for vehicle routing. Networks, 11, 109–124.

    MathSciNet  Google Scholar 

  • Fitzsimmons, J. A. (1973) A methodology for emergency ambulance deployment. Management Science 19, 627–636.

    Google Scholar 

  • Flynn, J. and Ratick, S. (1988) A multiobjective hierarchical covering model for the essential air services program. Transportation Science 22, 139–147.

    Google Scholar 

  • Fourer, R., Gay, D. M. and Kernighan, B. W. (1993) AMPL: A Modeling Language For Mathematical Programming. Scientific Press, San Francisco, CA.

    Google Scholar 

  • Galvão, R. D. and ReVelle, C. (1996) A Lagrangean heuristic for the maximal covering location problem. European Journal of Operational Research 88, 114–123.

    Article  Google Scholar 

  • Garey, M. R. and Johnson, D. S. (1979) Computers and Intractability: A Guide to the Theory ofNP-Completeness. W. H. Freeman and Co., New York.

    Google Scholar 

  • Gendreau, M., Hertz, A. and Laporte, G. (1994) A tabu search heuristic for the vehicle routing problem. Management Science 40, 1277–1290.

    Google Scholar 

  • Ghosh, A. and McLafferty, S. L. (1982) Locating stores in uncertain environments: A scenario planning approach. Journal of Retailing 58:4, 5–22.

    Google Scholar 

  • Gillet, B. E. and Miller, L. R. (1974) A heuristic algorithm for the vehicle dispatch problem. Operations Research 22, 340–350.

    Google Scholar 

  • Golden, B. L., and Assad, A. A. (eds.) (1988) Vehicle Routing: Methods and Studies. Studies in Management Science and Systems, North Holland, Amsterdam.

    Google Scholar 

  • Gunawardane, G. (1982) Dynamic versions of set covering type public facility location problems. European Journal of Operational Research 10, 190–195.

    Article  MATH  Google Scholar 

  • Hakimi, S. (1965) Optimum location of switching centers in a communications network and some related graph theoretic problems. Operations Research 13, 462–475.

    MATH  MathSciNet  Google Scholar 

  • Hakimi, S. (1964) Optimum location of switching centers and the absolute centers and medians of a graph. Operations Research 12, 450–459.

    MATH  Google Scholar 

  • Handler, G. Y. (1990) P-center problems. Discrete Location Theory eds. P. B. Mirchandani and R. L. Francis, pp. 305–347, John Wiley, New York.

    Google Scholar 

  • Handler, G. Y. and Mirchandani, P. B. (1979) Location on Networks. M.I.T. Press, Cambridge, MA.

    Google Scholar 

  • Hansen, P. and Mladenovic, N. (1997) Variable neighborhood search for the p-median. Location Science 5, 207–226.

    Article  Google Scholar 

  • Hansen, P., Peeters, D. and Thisse, J. F. (1982) An algorithm for the constrained Weber problem. Management Science 28, 1285–1295.

    Google Scholar 

  • Hertz, J. H. (1964) The Pentateuch and Haftorahs. Soncino Press, London.

    Google Scholar 

  • Hurter, A. P., Schaefer, M. K. and Wendell, R. E. (1975) Solutions of constrained location problems. Management Science 22, 51–56.

    MathSciNet  Google Scholar 

  • Hsu, V. N., Daskin, M. S., Jones, P. C. and Lowe, T. J. (1995) Tool selection for optimal part production: A Lagrangian relaxation approach. IIE Transactions 27, 417–426.

    Google Scholar 

  • Jornsten, K. and Bjorndal, M. (1994) Dynamic location under uncertainty. Studies in Regional and Urban Planning 3, 163–184.

    Google Scholar 

  • Kendall, M. G. and Moran, P. A. P. (1963) Geometrical Probability. Griffin’s Statistical Monographs and Courses, Charles Griffin and Company Ltd., London.

    Google Scholar 

  • Kouvelis, P. and Yu, G. (1996) Robust Discrete Optimization and Its Applications. Kluwer Academic Publishers, Boston, MA.

    Google Scholar 

  • Kuby, M. J. and Gray, R. G. (1993) The hub network design problem with stop feeders: The case of Federal Express. Transportation Research 27A, 1–12.

    Google Scholar 

  • Krarup, J. and Pruzan, P. M. (1990) Ingredients of location analysis. Discrete Location Theory eds. P.B. Mirchandani and R. L. Francis, pp. 1–54, Wiley, New York.

    Google Scholar 

  • Laporte, G. (1988) Location-routing problems. Vehicle Routing: Methods and Studies eds. B. L. Golden and A. A. Assad, pp. 163–197, Elsevier Science Publishers, North Holland, Amsterdam.

    Google Scholar 

  • Laporte, G. and Dejax, P. J. (1989) Dynamic location-routing problems. Journal of the Operational Research Society 40:5, 471–482.

    Google Scholar 

  • Laporte, G., Nobert, Y. and Tallefer, S. (1988) Solving a family of multi-depot vehicle routing and location-routing problems. Transportation Science 22, 161–172.

    MathSciNet  Google Scholar 

  • Lawler, E. L., Lenstra, J. K., Rinnoy Kan, A. H. G. and Shmoys, D. B. (eds.) (1985) The Traveling Salesman Problem: A Guided Tow of Combinatorial Optimization. John Wiley and Sons, Inc., New York.

    Google Scholar 

  • Larson, R. C. (1974) A hypercube queuing model for facility location and redistricting in urban emergency services, Computers and Operations Research 1, 67–95.

    Article  MathSciNet  Google Scholar 

  • Larson, R. C. (1975) Approximating the performance of urban emergency service systems, Operations Research 23, 845–868.

    MATH  Google Scholar 

  • Larson, R. C. and Sadiq, G. (1983) Facility location with the Manhattan metric in the presence ofbarriers to travel. Operations Research 31, 652–669.

    MathSciNet  Google Scholar 

  • Lerman, S. (1976) Location, housing, auto ownership and mode to work: A joint choice model. Transportation Research Record, 610, Washington, D.C.

    Google Scholar 

  • Lin, S. and Kernighan, B. W. (1973) An effective heuristic algorithm for the traveling salesman problem. Operations Research 21, 498–516.

    MathSciNet  Google Scholar 

  • List, G. F., Mirchandani, P. B., Turnquist, M. A. and Zografos, K. G. (1991) Modeling and analysis for hazardous materials transportation: Risk analysis, routing/scheduling and facility location. Transportation Science 25, 100–114.

    Google Scholar 

  • Louveaux, F. V. (1986) Discrete stochastic location models. Annals of Operations Research 6, 23–34.

    Article  Google Scholar 

  • Manheim, M. L. (1979) Fundamentals ofTransportation Systems Analysis. M.I.T. Press, Cambridge, MA.

    Google Scholar 

  • Manne, A. S. (1961) Capacity expansion and probabilistic growth. Econometrica 29, 632–649.

    MATH  MathSciNet  Google Scholar 

  • Maranzana, F. E. (1964) On the location of supply points to minimize transport costs. Operational Research Quarterly 15, 261–270.

    Google Scholar 

  • Marianov, V. and ReVelle, C. S. (1992) A probabilistic fire-protection siting model with joint vehicle reliability requirements. Papers in Regional Science: The Journal of the RSAI 71, 217–241.

    Google Scholar 

  • Marianov, V. and ReVelle, C. S. (1996) The queueing maximal availability location problem: A model for siting of emergency vehicles. European Journal of Operational Research 93, 110–120.

    Article  Google Scholar 

  • Maze, T. H., Khasnabis, S., Kapur, K. C. and Kutsal, M. (1982) A methodology for locating and sizing fixed facilities and the Detroit case study. Final report, Urban Mass Transportation Administration, Grant Number MI-11-0004, Wayne State University, Detroit, MI.

    Google Scholar 

  • Maze, T. H., Khasnabis, S., Kapur, K. and Poola, M. S. (1981) Proposed approach to determine the optimal number, size and location of bus garage additions. Transportation Research Record 781, Washington, D.C.

    Google Scholar 

  • Megiddo, N., Zemel, E. and Hakimi, S. L. (1983) The maximal coverage location problem. SIAM Journal of Algebraic and Discrete Methods 4, 253–261.

    MathSciNet  Google Scholar 

  • Melkote, S. (1996) Integrated Models of Facility Location and Network Design. Ph.D. dissertation, Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL 60208.

    Google Scholar 

  • Min, H. (1988) The dynamic expansion and relocation of capacitated public facilities: A multi-objective approach. Computers and Operations Research 15, 243–252.

    Article  Google Scholar 

  • Mirchandani, P. B. (1980) Locational decisions on stochastic networks. Geographical Analysis 12, 172–183.

    Google Scholar 

  • Mirchandani, P. and Odoni, A. (1979) Location of medians on stochastic networks. Transportation Science 13, 85–97.

    MathSciNet  Google Scholar 

  • O’Kelly, M. E. (1986a) Activity levels at hub facilities in interacting networks. Geographical Analysis 18, 343–356.

    Google Scholar 

  • O’Kelly, M. E. (1986b) The location of interacting hub facilities. Transportation Science 20, 92–106.

    Google Scholar 

  • O’Kelly, M. E. (1987) A quadratic integer program for the location of interacting hub facilities. European Journal of Operational Research 32, 393–404.

    MathSciNet  Google Scholar 

  • O’Kelly, M. E. and Miller, H. M. (1994) The hub network design problems: A review and synthesis. The Journal of Transport Geography 2, 31–40.

    Google Scholar 

  • Osleeb, J. and Ratick, S. (1990) A dynamic location-allocation model for evaluating the spatial impacts of just-in-time planning. Geographical Analysis 22, 50–69.

    Google Scholar 

  • Owen, S. H. (1998) Scenario Planning Approaches to Facility Location: Models and Solution Methods. Ph.D. dissertation, Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL 60208.

    Google Scholar 

  • Owen, S. H. and Daskin, M. S. (1998) Strategic facility location: A review, European Journal of Operational Research 111, 423–447.

    Article  Google Scholar 

  • Owen, S. H. and Daskin, M. S. (1998) Strategic facility location via evolutionary programming. Working paper, Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL, 60208.

    Google Scholar 

  • Peeters, D. and Thomas, 1. (1995) The effect of spatial structure on location-allocation results. Transportation Science 29, 366–373.

    Google Scholar 

  • Perl, J. and Daskin, M. S. (1985) A warehouse location-routing model. Transportation Research, 19B, 381–396.

    Google Scholar 

  • Plane, D. R. and Hendrick, T. E. (1977) Mathematical programming and the location offire companies for the Denver fire department. Operations Research 25, 563–578.

    Google Scholar 

  • Plaut, W. G. (ed.) (1981) The Torah: A Modern Commentary. Union of American Hebrew Congregations, New York.

    Google Scholar 

  • Ratick, S. J., Du, W. and Moser, D. A. (1992) Development of a reliability based dynamic dredging decision model. European Journal of Operational Research 58, 318–334.

    Article  Google Scholar 

  • Ratick, S., Osleeb, J., Kuby, M. and Lee, K. (1987) Interperiod Network Storage Location-Allocation (1NSLA) Models. Spatial Analysis andLocation Allocation Models eds. G. Rushton and A. Ghosh, pp. 269–301. Van Nostrand Reinhold Company, New York.

    Google Scholar 

  • Ratick, S, J. and White, A. L. (1988) A risk-sharing model for locating noxious facilities. Environment and Planning B, 15, 165–179.

    Google Scholar 

  • ReVelle, C., Cohon, J. and Shobrys, D. (1991) Simultaneous siting and routing in the disposal of hazardous wastes. Transportation Science 25, 138–145.

    Google Scholar 

  • ReVelle, C. S. and Hogan, K. (1989a) The maximum availability location problem. Transportation Science 23, 192–200.

    MathSciNet  Google Scholar 

  • ReVelle, C. S. and Hogan, K. (1989b) The maximum reliability location problem and α-reliable P-center problem: Derivatives of the probabilistic location set covering problem. Annals of Operations Research 18, 155–174.

    Article  MathSciNet  Google Scholar 

  • Roodman, G. M. and Schwarz, L. B. (1975) Optimal and heuristic facility phase-out strategies. A11E Transactions 7, 177–184.

    Google Scholar 

  • Schilling, D. A. (1980) Dynamic location modeling for public sector facilities: A multicriteria approach. Decision Sciences 11, 714–724.

    Google Scholar 

  • Schilling, D. A. (1982) Strategic facility planning: The analysis of options. Decision Sciences 13, 1–14.

    Google Scholar 

  • Scott, A. J. (1971) Dynamic location-allocation systems: Some basic planning strategies. Environment and Planning 3, 73–82.

    Google Scholar 

  • Serra, D. and Marianov, V. (1997) The P-median problem in a changing network: The case of Barcelona. Submitted for publication to Location Science.

    Google Scholar 

  • Serra, D., Rattick, S. and ReVelle, C. (1996) The maximum capture problem with uncertainty. Environment and Planning B 23, 49–59.

    Google Scholar 

  • Sheppard, E. S. (1974) A conceptual framework for dynamic location-allocation analysis. Environment and Planning A 6, 547–564.

    Google Scholar 

  • Skorin-Kapov, D. and Skorin-Kapov, J. (1994) On tabu search for the location of interacting hub facilities. European Journal of Operational Research 73, 502–509.

    Article  Google Scholar 

  • Sweeney, D. J. and Tatham, R. L. (1976) An improved long-run model for multiple warehouse location. Management Science 22, 748–758.

    MathSciNet  Google Scholar 

  • Srivastava, R. (1993) Alternate solution procedures for the location-routing problem. OMEGA 21, 497–506.

    Article  Google Scholar 

  • Taillard, É., Badeau, P., Gendreau, M., Guertin, F. and Potvin, J. Y. (1997) A tabu search heuristic for the vehicle routing problem with soft time windows. Transportation Science 31, 159–169.

    Google Scholar 

  • Tapiero, C. S. (1971) Transportation-location-allocation problems over time. Journal of Regional Science 11, 377–384.

    Google Scholar 

  • Teitz, M. B. and Bart, P. (1968) Heuristic methods for estimating generalized vertex median ofa weighted graph. Operations Research 16, 955–961.

    Google Scholar 

  • Toregas, C., Swain, R., ReVelle, C. and Bergman, L. (1971) The location of emergency service facilities. Operations Research 19, 1363–1373.

    Google Scholar 

  • van der Heijden, K. (1994) Probabilistic planning and scenario planning. Subjective Probability, eds. G. Wright and P. Ayton, pp. 549–572, Wiley, New York.

    Google Scholar 

  • Van Roy, T. J. and Erlenkotter, D. (1982) A dual-based procedure for dynamic facility location. Management Science 28, 1091–1105.

    Google Scholar 

  • Vanston, J. H., Frisbie, W. P., Lopreato, S. C. and Poston, D. L. (1977) Alternate scenario planning. Technological Forecasting and Social Change 10, 159–180.

    Google Scholar 

  • Watson, M. (1996) A Standardization Analysis Process Applied to Steel Coils in the Automotive Industry. Ph.D. dissertation, Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, 1L 60208.

    Google Scholar 

  • Weaver, J. and Church, R. (1983) Computational procedures for location problems on stochastic networks. Transportation Science 17, 168–180.

    Google Scholar 

  • Webb, M. H. J. (1968) Cost functions in the location of depot for multiple-deliveryjourneys. Operational Research Society 19, 311–320.

    Google Scholar 

  • Weber, A. (1929) Uber den Standort der Industrien (Alfred Weber’s Theory of the Location of Industries). University of Chicago, Chicago, IL.

    Google Scholar 

  • Wesolowsky, G. O. (1973) Dynamic facility location. Management Science 19, 1241–1248.

    Google Scholar 

  • Wesolowsky, G. O. and Truscott W. G. (1976) The multiperiod location-allocation problem with relocation of facilities. Management Science 22, 57–65.

    Google Scholar 

  • Xu, J. and Kelly, J. P. (1996) A network flow-based tabu search heuristic for the vehicle routing problem. Transportation Science 30, 379–393.

    Google Scholar 

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  1. Mark S. Daskin
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  1. University of Southern California, USA

    Randolph W. Hall

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Daskin, M.S., Owen, S.H. (2003). Location Models in Transportation. In: Hall, R.W. (eds) Handbook of Transportation Science. International Series in Operations Research & Management Science, vol 56. Springer, Boston, MA. https://doi.org/10.1007/0-306-48058-1_10

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  • Online ISBN: 978-0-306-48058-4

  • eBook Packages: Springer Book Archive

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