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Branch-and-Price Heuristics: A Case Study on the Vehicle Routing Problem with Time Windows

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Abstract

Branch-and-price is a powerful framework to solve hard combinatorial problems. It is an interesting alternative to general purpose mixed integer programming as column generation usually produces at the root node tight lower bounds (when minimizing) that are further improved when branching. Branching also helps to generate integer solutions, however branch-and-price can be quite weak at producing good integer solutions rapidly because the solution of the relaxed master problem is rarely integer-valued. In this paper, we propose a general cooperation scheme between branch-and-price and local search to help branch-and-price finding good integer solutions earlier. This cooperation scheme extends to branch-and-price the use of heuristics in branch-and-bound and it also generalizes three previously known accelerations of branch-and-price. We show on the vehicle routing problem with time windows (Solomon benchmark) that it consistently improves the ability of branch-and-price to generate good integer solutions ea rly while retaining the ability of branch-and-price to produce good lower bounds.

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References

  • Aarts, E. and Lenstra, J. (1997). Local Search in Combinatorial Optimization. Wiley.

    Google Scholar 

  • Alt, H., Guibas, L., Mehlhorn, K., Karp, R., and Wigderson, A. (1996). A method for obtaining randomized algorithms with small tail probabilities. Algorithmica, 16(4–5):543–547.

    Article  MathSciNet  Google Scholar 

  • Balas, E. and Martin, C. (1980). Pivot and complement—A heuristic for 0–1 programming. Management Science, 26(1):89–96.

    MathSciNet  Google Scholar 

  • Barnhart, C., Johnson, E., Nemhauser, G., Savelsbergh, M., and Vance, P. (1998). Branch-and-price: Column generation for solving huge integer programs. Operations Research, 46:316–329.

    MathSciNet  Google Scholar 

  • Bixby, R., Fenelon, M., Gu, Z., Rothberg, E., and Wunderling, R. (2000). MIP: Theory and pratice-Closing the gap. System, Modelling and Optimization: Methods, Theory, and Applications, pp. 19–49, Kluwer Academic Publishers.

    Google Scholar 

  • Bräysy, O. and Gendreau, M. (2003a). Vehicle routing with time windows, part I: Route construction and local search algorithms. Technical Report, SINTEF Applied Mathematics, Department of Optimization, Oslo, Norway.

    Google Scholar 

  • Bräysy, O. and Gendreau, M. (2003b). Vehicle routing with time windows, part II: Metaheuristics. Technical Report, SINTEF Applied Mathematics, Department of Optimization, Oslo, Norway.

    Google Scholar 

  • Chabrier, A. (2003). Vehicle routing problem with elementary shortest path based column generation. Forthcoming in: Computers and Operations Research.

    Google Scholar 

  • Chabrier, A., Danna, E., and Le Pape, C. (2002). Coopération entre géneration de colonnes avec tournées sans cycle et recherche locale appliquée au routage de véhicules Huitièmes Journées Nationales sur la resolution de Problèmes NP-Complets (JNPC’2002), pp.83–97.

    Google Scholar 

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

    Google Scholar 

  • Cook, W. and Rich, J. (1999). A parallel cutting-plane algorithm for the vehicle routing problem with time windows. Technical Report TR99-04, Department of Computational and Applied Mathematics, Rice University.

    Google Scholar 

  • Cordeau, J.-F., Desaulniers, G., Desrosiers, J., Solomon, The Vehicle Routing Problem (M., and Soumis, F. (2002). The VRP with time windows. In: Toth, P. and Vigo, D., eds.), pp. 157–193, SIAM Monographs on Discrete Mathematics and Applications.

    Google Scholar 

  • Cordeau, J.-F., Laporte, G., and Mercier, A. (2001). A unified tabu search heuristic for vehicle routing problems with time windows. Journal of the Operational Research Society, 52:928–936.

    Article  Google Scholar 

  • Croes, G. (1958). A method for solving traveling-salesman problems. Operations Research, 6:791–812.

    MathSciNet  Google Scholar 

  • De Backer, B., Furnon, V., Shaw, P., Kilby, Ph., and Prosser, P. (2000). Solving vehicle routing problems using constraint programming and metaheuristics. Journal of Heuristics, 6:501–523.

    Article  Google Scholar 

  • Desaulniers, G., Desrosiers, J., and Solomon, M. (2002). Accelerating strategies for column generation methods in vehicle routing and crew scheduling problems. In: Essays and Surveys in Metaheuristics (C. Ribeiro and P. Hansen, eds.), pp. 309–324, Kluwer Academic Publishers.

    Google Scholar 

  • Desrochers, M. (1986). La fabrication d’horaires de travail pour les conducteurs d’autobus par une méthode de génération de colonnes. Ph.D Thesis, Université de Montréal, Canada.

    Google Scholar 

  • Desrochers, M., Desrosiers, J., and Solomon, M. (1992). A new optimization algorithm for the vehicle routing problem with time windows. Operations Research, 40:342–354.

    MathSciNet  Google Scholar 

  • Desrosiers, J. and Lübbecke, M. (2004). A primer in column generation. Les Cahiers du GERAD, G-2004-02, HEC, Montréal, Canada.

    Google Scholar 

  • Feillet, D., Dejax, P., Gendreau, M., and Gueguen, C. (2004). An exact algorithm for the elementary shortest path problem with resource constraints: Application to some vehicle routing problems. Networks, 44(3):216–229.

    Article  MathSciNet  Google Scholar 

  • Gambardella, L., Taillard, E., and Agazzi, G. (1999). MACS-VRPTW: A multiple ant colony system for vehicle routing problems with time windows. In: New Ideas in Optimization (D. Corne, M. Dorigo,, and F. Glover, eds.), PP. 63–76, McGraw-Hill.

    Google Scholar 

  • Glover, F. and Laguna, M. (1997). Tabu Search, Kluwer Academic Publishers.

    Google Scholar 

  • Hadjar, A., Marcotte, O., and Sournis, F. (2001). A branch-and-cut algorithm for the multiple depot vehicle scheduling problem. Les Cahiers du GERAD, G-2001-25, HEC, Montréal, Canada.

    Google Scholar 

  • Homberger, J. and Gehring, H. (1999). Two evolutionary metaheuristics for the vehicle routing problem with time windows. INFOR, 37:297–318.

    Google Scholar 

  • Houck, D., Picard, J., Queyranne, M., and Vemuganti, R. (1980). The travelling salesman problem as a constrained shortest path problem: Theory and computational experience. Opsearch 17:93–109.

    MathSciNet  Google Scholar 

  • ILOG, S.A. (2002). ILOG DISPATCHER 3.3 User’s Manual.

    Google Scholar 

  • Irnich, S. (2001). The shortest path problem with κ-cycle elimination (κ ≥ 3): Improving a branch and price algorithm for the VRPTW. Technical Report, Lehr-und Forschungsgebiet Unternehmensforschung Rheinish-Westfälishe Technische Hochshule, Aachen, Germany.

    Google Scholar 

  • Irnich, S. and Villeneuve, D. (2003). The shortest path problem with resource constraints and κ-cycle elimination for κ ≥ 3. Les Cahiers du GERAD, G-2003-55, HEC, Montréal, Canada.

    Google Scholar 

  • Kallehauge, B., Larsen, J., and Madsen, O. (2001). Lagrangean duality and non-differentiable optimization applied on routing with time windows—Experimental results. Technical Report IMM-TR-2001-9,Department of Mathematical Modelling, Technical University of Denmark, Lyngby, Denmark.

    Google Scholar 

  • Kohl, N., Desrosiers, J., Madsen, O.B.G., Solomon, M., and Soumis, F. (1999). 2-path cuts for the vehicle routing problem with time windows. Transportation Science, l(13):101–116.

    Article  Google Scholar 

  • Larsen, J. (1999). Parallelization of the vehicle routing problem with time windows. Ph.D Thesis, Informatics and Mathematical Modelling, Technical University of Denmark, DTU.

    Google Scholar 

  • Lin, S. (1965). Computer solutions of the traveling salesman problem. Bell System Technical Journal, 44:2245–2269.

    MATH  MathSciNet  Google Scholar 

  • Or, I. (1976). Traveling salesman-type problems and their relation to the logistics of regional blood banking. Ph.D Thesis, Department of Industrial Engineering and Management Sciences, Northwestern University.

    Google Scholar 

  • Paessens, H. (1988). The savings algorithm for the vehicle routing problem. European Journal of Operational Research, 34:336–344.

    Article  MATH  Google Scholar 

  • Rochat, Y. and Taillard, E. (1995). Probabilistic diversification and intensification in local search for vehicle routing. Journal of Heuristics, 1:147–167.

    Google Scholar 

  • Røpke, S. (2003). A General Heuristic for Vehicle Routing Problems. International Workshop on Vehicle Routing and Multimodal Transporation (ROUTE’2003).

    Google Scholar 

  • Rousseau, L.-M., Gendreau, M., and Pesant, G. (2002). Solving small VRPTWs with constraint programming based column generation. In: Proceedings of the Fourth International Workshop on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (CP-AI-OR’02) (N. Jussien and F. Laburthe, F.,eds.), pp. 333–344.

    Google Scholar 

  • Savelsbergh, M. and Sol, M. (1998). Drive: Dynamic routing of independent vehicles. Operations Research, 46(4):474–490.

    Google Scholar 

  • Shaw, P. (1998). Using constraint programming and local search methods to solve vehicle routing problems. In: Proceedings of the Fourth International Conference on Principles and Practice of Constraint Programming (CP’98), pp. 417–431. Forthcoming in: INFORMS Journal of Computing.

    Google Scholar 

  • Solomon, M. (1987). Algorithms for the vehicle routing and scheduling problem with time window constraints. Operations Research, 35:254–265.

    MATH  MathSciNet  Google Scholar 

  • Voß, S., Martello, S., Osman, I., and Roucairol, C. (1999). Metaheuristics: Advances and Trends in Local Search Paradigms for Optimization. Kluwer Academic Publishers.

    Google Scholar 

  • Voudouris, C. (1997). Guided local search for combinatorial optimization problems. Ph.D Thesis, Department of Computer Science, University of Essex, Colchester, UK.

    Google Scholar 

  • Xu, H., Chen, Z., Rajagopal, S., and Arunapuram, S. (2003). Solving a practical pickup and delivery problem. Transportation Science, 37(3):347–364.

    Article  Google Scholar 

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Danna, E., Le Pape, C. (2005). Branch-and-Price Heuristics: A Case Study on the Vehicle Routing Problem with Time Windows. In: Desaulniers, G., Desrosiers, J., Solomon, M.M. (eds) Column Generation. Springer, Boston, MA. https://doi.org/10.1007/0-387-25486-2_4

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