[en] This paper investigates a multi-period vehicle loading problem with stochastic information regarding the release dates of items to be transported. The deterministic version of the problem can be formulated as a large-scale set covering problem. Several heuristic algorithms are proposed to generate decision policies for the stochastic optimization model
over a long rolling horizon. The resulting policies have been extensively tested on instances which display the main characteristics of the industrial case-study that motivated the research. The tests demonstrate the benefits of the multi-period stochastic model over simple myopic strategies. A simple and efficient heuristic is shown to deliver good policies and to be robust against errors in the estimation of the probability distribution of the release dates.
Research Center/Unit :
QuantOM- HEC-ULiège
Disciplines :
Production, distribution & supply chain management Quantitative methods in economics & management
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Bibliography
Angelelli E, Bianchessi N, Mansini R, Speranza M (2009) Short term strategies for a dynamic multi-period routing problem. Transp Res 17:106–119
Angelelli E, Savelsbergh M, Speranza M (2007) Competitive analysis for dynamic multi-period uncapacitated routing problems. Networks 49:308–317
Barr RS, Golden BL, Kelly JP, Resende MGC, Stewart WR (1995) Designing and reporting on computational experiments with heuristic methods. J Heuristics 1:9–32
Bertsimas D, Brown D, Caramanis C (2011) Theory and applications of robust optimization. SIAM Rev 53:464–501
Birge JR, Louveaux F (1997) Introduction to stochastic programming. Springer, Berlin
Boudia M, Louly M, Prins C (2007) A reactive GRASP and path relinking for a combined production-distribution problem. Comput Oper Res 34:3402–3419
Brownlee J (2007) A note on research methodology and benchmarking optimization algorithms. Technical Report, Swinburne University of Technology
Chen Z-L (2004) Integrated production and distribution operations: taxonomy, models and review. In: Simchi-Levi D, Wu S, Shen Z-J (eds) Handbook of quantitative supply chain analysis: modeling in the E-business era chapter 17. Kluwer Academic Publishers, Amsterdam, pp 711–746
Chen Z-L (2010) Integrated production and outbound distribution scheduling: Review and extensions. Oper Res 58:130–148
Cordeau J-F (2007) The dial-a-ride problem: models and algorithms. Annals Oper Res 153:29–46
Crainic T (2003) Long-haul freight transportation. In: Hall R (ed) Handbook of transportation science international series in operations research and management science. Kluwer Academic Publishers, Boston, pp 451–516
Dyckhoff H (1990) A typology of cutting and packing problems. Eur J Oper Res 44:145–159
Erengüç SS, Simpson NC, Vakharia AJ (1999) Integrated production/distribution planning in supply chains: an invited review. Eur J Oper Res 115:219–236
Frantzeskakis L, Powell W (1990) A successive linear approximation procedure for stochastic dynamic vehicle allocation problems. Transp Sci 24:40–57
Fumero F, Vercellis C (1999) Synchronized development of production, inventory and distribution schedules. Transp Sci 33:330–340
Gendreau M, Potvin J-Y (1998) Dynamic vehicle routing and dispatching. In: Crainic T, Laporte G (eds) Fleet management and logistics. Springer, Boston, pp 115–126
Heitsch H, Romisch W (2007a) A note on scenario reduction for two-stage stochastic programs. Oper Res Lett 35:731–738
Heitsch H, Romisch W (2007b) Scenario tree modeling for multistage stochastic programs. Math Program 118:371–406
Hooker JN (1995) Testing heuristics: We have it all wrong. Technical Report, Carnegie Mellon University
Johnson DS (2001) A theoretician’s guide to the experimental analysis of algorithms. Technical Report, AT and T Labs
Kouvelis P, Yu G (1997) Robust discrete optimization and its applications. Kluwer Academic Publisher, Dordrecht
Melo R, Wolsey L (2010). Optimizing production and transportation in a commit-to-delivery business mode. Eur J Oper Res 203:614–618
Pillac V, Gendreau M, Guret C, Medaglia A (2011) A revieuw of dynamic vehicle routing problems. Technical Report CIRRELT-2011-62 CIRRELT
Powell W (2011) Approximate dynamic programming. Wiley Series in Probability and Statistics, 2nd edn. John Wiley & Sons, Inc, Hoboken
Powell W, Topaloglu H (2003) Stochastic programming in transportation and logistics. In: Handbooks in operations research and management science, Vol 10. Elsevier, Amsterdam, pp 555–636
Psaraftis H (1995) Dynamic vehicle routing: status and prospects. Annals Oper Res 61:143–164
Rardin RL, Uzsoy R (2001) Experimental evaluation of heuristic optimization algorithms: A tutorial. J Heuristics 7:261–304
Rhee W (1988) Optimal bin packing with items of random sizes. Math Oper Res 13:140–151
Ruml W (2010) The logic of benchmarking: a case against state-of-the-art performance. Technical Report, Association for the Advancement of Artificial Intelligence
Sarmiento AM, Nagi R (1999) A review of integrated analysis of production-distribution systems. IIE Trans 31:1061–1074
Sethi S, Sorger G (1991) A theory of rolling horizon decision making. Annals Oper Res 29:387–416
Shapiro A (2003) Inference of statistical bounds for multistage stochastic programming problems. Math Methods Oper Res (ZOR) 58:57–68
Stecke K, Zhao X (2007) Production and transportation integration for a make-to-order manufacturing company with a commit-to-delivery business mode. Manuf Service Oper Manag 9:206–224
Tang J, Yung K-L, Ip AWH, Liu S (2007) Synchronized production and transportation planning using subcontracted vehicles in a production-distribution network. Transp Plan Technol 30:113–146
Van Hentenryck P, Bent R (2006) Online stochastic combinatorial optimization. Massachusetts Institute of Technology, Cambridge
Vanderbeck F (1999) Computational study of a column generation algorithm for bin packing and cutting stock problems. Math Program Series A 86:565–594
Vanderbeck F, Wolsey LA (1995) An exact algorithm for IP column generation. Oper Res Lett 19:151–159
Verweij B, Ahmed S, Kleywegt AJ, Nemhauser G, Shapiro A (2002) The sample average approximation method applied to stochastic routing problems: a computational study. Comput Optim Appl 24:289–333
Vidal C, Goetschalckx M (1997) Strategic production-distribution models: a critical review with emphasis on global supply chain models. Eur J Oper Res 98:1–18
Wang X, Cheng TCE (2009) Logistics scheduling to minimize inventory and transport costs. Int J Prod Econ 121:266–273
Wascher G, Hausner H, Schumann H (2007) An improved typology of cutting and packing problems. Eur J Oper ResEur J Oper Res 183:1109–1130
Wen M, Cordeau J-F, Laporte G, Larsen J (2010) The dynamic multi-period vehicle routing problem. Comput Oper Res 37:1615–1623
Yung K-L, Tang J, Ip AWH, Wang D (2006) Heuristics for joint decisions in production, transportation, and order quantity. Transp Sci 40:99–116
Zegordi SH, Abadi INK, Nia MAB (2010) A novel genetic algorithm for solving production and transportation scheduling in a two-stage supply chain. Comput Ind Eng 58:373–381
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