Publication: Heuristics for dynamic and stochastic routing in industrial shipping
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2013-01
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Pergamon-Elsevier
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Maritime transportation plays a central role in international trade, being responsible for the majority of long-distance shipments in terms of volume. One of the key aspects in the planning of maritime transportation systems is the routing of ships. While static and deterministic vehicle routing problems have been extensively studied in the last decades and can now be solved effectively with metaheuristics, many industrial applications are both dynamic and stochastic. In this spirit, this paper addresses a dynamic and stochastic maritime transportation problem arising in industrial shipping. Three heuristics adapted to this problem are considered and their performance in minimizing transportation costs is assessed. Extensive computational experiments show that the use of stochastic information within the proposed solution methods yields average cost savings of 2.5% on a set of realistic test instances.
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A. Azaron and F. Kianfar. Dynamic shortest path in stochastic dynamic networks: Ship routing problem. European Journal of Operational Research, 144:138-156, 2003.
R.W. Bent and P. Van Hentenryck. Scenario-based planning for partially dynamic vehicle routing with stochastic customers. Operations Research, 52:977-987, 2004.
G. Berbeglia, J.-F. Cordeau, and G. Laporte. Dynamic pickup and delivery problems. European Journal of Operational Research, 202:8-15, 2010.
L. Cheng and M.A. Duran. Logistics for world-wide crude oil transportation using discrete event simulation and optimal control. Computers and Chemical Engineering, 28:897-911, 2004.
M. Christiansen, K. Fagerholt, and D. Ronen. Ship routing and scheduling: Status and perspectives. Transportation Science, 38:1-18, 2004.
M. Christiansen, K. Fagerholt, B. Nygreen, and D. Ronen. Maritime transportation. In C. Barnhart and G. Laporte, editors, Handbooks in Operations Research and Management Science, pages 189-284. Elsevier, Amsterdam, 2007.
J.-F. Cordeau, G. Laporte, and A. Mercier. A unified tabu search heuristic for vehicle routing problems with time windows. Journal of the Operational Research Society, 52:928-936, 2001.
K. Fagerholt. A computer-based decision support system for vessel fleet scheduling – experience and future research. Decision Support Systems, 37:35-47, 2004.
K. Fagerholt and H. Lindstad. TurboRouter: An interactive optimisation-based decision support system for ship routing and scheduling. Maritime Economics and Logistics, 9:214-233, 2007.
T. Flatberg, G. Hasle, O. Kloster, E.J. Nilssen, and A. Riise. Dynamic and stochastic vehicle routing in practice. In V.S. Zeimpekis, C.D. Tarantilis, G.M. Giaglis, and I.E. Minis, editors, Dynamic Fleet Managament: Concepts, Systems, Algorithms & Case Studies, volume 38 of Operations Research Computer Science Interfaces Series, chapter 3, pages 41-64. Springer, New York, 2007.
M. Gendreau, G. Laporte, and R. Séguin. Stochastic vehicle routing. European Journal of Operational Research, 88:3-12, 1996.
M. Gendreau, F. Guertin, J.-Y. Potvin, and R. Seguin. Neighborhood search heuristics for a dynamic vehicle dispatching problem with pick-ups and deliveries.Transportation Research Part C, 14:157-174, 2006.
G. Ghiani, F. Guerriero, G. Laporte, and R. Musmanno. Real-time vehicle routing: Solution concepts, algorithms and parallel computing strategies. European Journal of Operational Research, 151:1-11, 2003.
L.M. Hvattum, A. Lokketangen, and G. Laporte. Solving a dynamic and stochastic vehicle routing problem with a sample scenario hedging heuristic. Transportation Science, 40:421-438, 2006.
L.M. Hvattum, A. Lokketangen, and G. Laporte. A branch-and-regret heuristic for stochastic and dynamic vehicle routing problems. Networks, 49:330-340, 2007.
H.-S. Hwang, S. Visoldilokpun, and J.M. Rosenberger. A branch-and-price-and-cut method for ship scheduling with limited risk. Transportation Science, 42:336-351, 2008.
S. Ichoua, M. Gendreau, and J.-Y. Potvin. Exploiting knowledge about future demands for real-time vehicle dispatching. Transportation Science, 40:211-225, 2006.
M.H. Kang, H.R. Choi, H.S. Kim, and B.J. Park. Development of a maritime transportation planning support system for car carriers based on genetic algorithm. Applied Intelligence,2011. DOI:10.1007/s10489-011-0278-z.
J.E. Korsvik, K. Fagerholt, and G. Laporte. A tabu search heuristic for ship routing and scheduling. Journal of the Operational Research Society, 61:594-603, 2010.
S.A. Lawrence. International Sea Transport: The Years Ahead. Lexington Books, Lexington, MA, 1972.
H.K. Lo and M.R. McCord. Adaptive ship routing through stochastic ocean currents: General formulations and empirical results. Transportation Research, Part A, 32:547-561, 1998.
O.B.G. Madsen, H.F. Ravn, and J.M. Rygaard. A heuristic algorithm for a dial-a-ride problem with time windows, multiple capacities and multiple objectives. Annals of Operations Research, 60:193-208, 1995.
S. Mitrovic-Minic and G. Laporte. Waiting strategies for the dynamic pickup and delivery problem with time windows. Transportation Research Part B, 38:635-655, 2004.
S. Mitrovic-Minic, R. Krishnamurti, and G. Laporte. Double horizon based heuristics for the dynamic pickup and delivery problem with time windows. Transportation Research Part B, 38:669-685, 2004.
W.B. Powell. A stochastic formulation of the dynamic assignment problem, with an application to truckload motor carriers. Transportation Science, 30:195-219, 1996.
H.N. Psaraftis. Dynamic vehicle routing problems. In B.L. Golden and A.A. Assad, editors, Vehicle Routing: Methods and Studies, pages 223-248. North-Holland, Amsterdam, 1988.
H.N. Psaraftis. Dynamic vehicle routing: Status and prospects. Annals of Operations Research, 61:143-164, 1995.
D. Ronen. Cargo ships routing and scheduling: Survey of models and problems. European Journal of Operational Research, 12:119-126, 1983.
D. Ronen. Ship scheduling: The last decade. European Journal of Operational Research, 71:325-333, 1993.
M.W.P. Savelsbergh and M. Sol. DRIVE: Dynamic routing of independent vehicles. Operations Research, 46:474-490, 1998.
M. Schilde, K.F. Doerner, and R.F. Hartl. Metaheuristics for the dynamic stochastic dial-a-ride problem with expected return transports. Computers and Operations Research, 38:1719-1730, 2011.
N. Secomandi and F. Margot. Reoptimization approaches for the vehicle-routing problem with stochastic demands. Operations Research, 57:214-230, 2009.
M.R. Swihart and J.D. Papastavrou. A stochastic and dynamic model for the single-vehicle pick-up and delivery problem. Europen Journal of Operational Research, 114:447-464, 1999.
B.W. Thomas. Waiting strategies for anticipating service requests from known customer locations. Transportation Science, 41:319-331, 2007.
UNCTAD. Review of maritime transportation. Technical report, UNCTAD, 2009.
P. Van Hentenryck, R.W. Bent, and E. Upfal. Online stochastic optimization under time constraints. Annals of Operations Research, 177:151-183, 2010.