Abstract
The paper deals with parallel variants of optimization algorithms dedicated to solve transportation optimization issues. The problem derives from practice of logistics and vehicle routes planning. We propose parallelization method of the cost function determination dedicated to be executed on GPU architecture. The method can be used in metaheuristic algorithms as well as in exact approaches.
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Alba, E., Dorronsoro, B.: Computing Nine New Best-So-Far Solutions for Capacitated VRP with a Cellular Genetic Algorithm. Information Processing Letters 98(6), 225–230 (2006)
Bożejko, W., Wodecki, M.: Parallel genetic algorithm for minimizing total weighted completion time. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds.) ICAISC 2004. LNCS (LNAI), vol. 3070, pp. 400–405. Springer, Heidelberg (2004)
Bożejko, W., Wodecki, M.: Parallel Evolutionary Algorithm for the Traveling Salesman Problem. Journal of Numerical Analysis, Industrial and Applied Mathematics 2(3-4), 129–137 (2007)
Bożejko, W., Wodecki, M.: Solving Permutational Routing Problems by Population-Based Metaheuristics. Computers & Industrial Engineering 57, 269–276 (2009)
Bożejko, W., Uchroński, M., Wodecki, M.: The new golf neighborhood for the flexible job shop problem. In: Proceedings of the ICCS 2010. Procedia Computer Science, vol. 1, pp. 289–296. Elsevier (2010)
Bożejko, W., Pempera, J., Smutnicki, C.: Parallel Tabu Search Algorithm for the Hybrid Flow Shop Problem. Computers & Industrial Engineering 65, 466–474 (2013)
Bożejko, W., Wodecki, M.: On the theoretical properties of swap multimuwes. Res. Lett. 35(2), 227–231 (2007)
Dantzig, G.B., Ramser, J.H.: The Truck Dispatching Problem, INFORMS. Management Science 6(1), 80–91 (1959)
Doerner, K.F., Hartl, R.F., Kiechle, G., Lucká, M., Reimann, M.: Parallel ant systems for the capacitated vehicle routing problem. In: Gottlieb, J., Raidl, G.R. (eds.) EvoCOP 2004. LNCS, vol. 3004, pp. 72–83. Springer, Heidelberg (2004)
Hasle, G., Kloster, O.: Industrial Vehicle Routing, SINTEF ICT, Department of Applied Mathematics, P.O. Box 124 Blindern, NO-0314 Oslo, Norway
Jagiełło, S., Źelazny, D.: Solving Multi-criteria Vehicle Routing Problem by Parallel Tabu Search on GPU. Procedia Computer Science (18), 2529–2532 (2013)
Le Bouthillier, A., Crainic, T.: A cooperative parallel meta-heuristic for the vehicle routing problem with time windows. Computers & Operations Research 32, 1685–1708 (2005)
Pempera, J., Smutnicki, C., Żelazny, D.: Optimizing bicriteria flow shop scheduling problem by simulated annealing algorithm. Procedia Computer Science (18), 936–945 (2013)
Rego, C.: Node-ejection chains for the vehicle routing problem: Sequential and parallel algorithms. Parallel Computing 27, 201–222 (2001)
Rudy, J., Żelazny, D.: Memetic algorithm approach for multi-criteria network scheduling. In: Proceeding of the International Conference on ICT Management for Global Competitiveness and Economic Growth in Emerging Economies (ICTM 2012), pp. 247–261 (2012)
Rudy, J., ?Zelazny, D.: GACO: a parallel evolutionary approach to multi-objective scheduling. In: Gaspar-Cunha, A., Henggeler Antunes, C., Coello, C.C. (eds.) EMO 2015. LNCS, vol. 9018, pp. 307–320. Springer, Heidelberg (2015)
Toth, P., Vigo, D.: Vehicle Routing Problem, Society for Industrial and Applied Mathematics, Philadelphia (2001)
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Wodecki, M., Bożejko, W., Jagiełło, S., Pempera, J. (2015). Parallel Cost Function Determination on GPU for the Vehicle Routing Problem. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2015. Lecture Notes in Computer Science(), vol 9120. Springer, Cham. https://doi.org/10.1007/978-3-319-19369-4_69
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DOI: https://doi.org/10.1007/978-3-319-19369-4_69
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19368-7
Online ISBN: 978-3-319-19369-4
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