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Growing Science » International Journal of Industrial Engineering Computations » Memetic algorithm for the dynamic vehicle routing problem with simultaneous delivery and pickup

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International Journal of Industrial Engineering Computations

ISSN 1923-2934 (Online) - ISSN 1923-2926 (Print)
Quarterly Publication
Volume 13 Issue 4 pp. 587-600 , 2022

Memetic algorithm for the dynamic vehicle routing problem with simultaneous delivery and pickup Pages 587-600 Right click to download the paper Download PDF

Authors: Amina Berahhou, Youssef Benadada, Khaoula Bouanane

DOI: 10.5267/j.ijiec.2022.6.001

Keywords: DVRP, DVRPSDP, Local search, Memetic algorithm, Reverse Logistics type

Abstract: In recent years, the Vehicle Routing Problem (VRP) has become an important issue for distribution companies. Also, the rapid development of communication means and the appearance of reverse logistics have given rise to new variants of the VRP. This article deals with an important variant of the VRP which is Dynamic Vehicle Routing Problem with Simultaneous Delivery and Pickup (DVRPSDP), in which new customers appear during the working day and each customer requires simultaneous delivery and pickup. A Memetic Algorithm (MA) that combines Genetic Algorithm (GA) and local search procedure have been proposed to solve the problem. The performance of the algorithm is evaluated with the tests carried out on a set of benchmarks found in the literature. The proposed memetic algorithm is very efficient and gives many good solutions.

How to cite this paper
Berahhou, A., Benadada, Y & Bouanane, K. (2022). Memetic algorithm for the dynamic vehicle routing problem with simultaneous delivery and pickup.International Journal of Industrial Engineering Computations , 13(4), 587-600.

Refrences
Aguiar, B. D. C. X. C., Siqueira, P. H., de França Aguiar, G., & de Souza, L. V. (2014). Particle swarm optimization for vehicle routing problem with fleet heterogeneous and simultaneous collection and delivery. Applied Mathematical Sciences, 8(77), 3833-3849.
Ai, T. J., & Kachitvichyanukul, V. (2009). A particle swarm optimization for the vehicle routing problem with simultaneous pickup and delivery. Computers & Operations Research, 36(5), 1693-1702.
Angelelli, E., & Mansini, R. (2002). The vehicle routing problem with time windows and simultaneous pick-up and delivery. In Quantitative approaches to distribution logistics and supply chain management (pp. 249-267). Springer, Berlin, Heidelberg.
Augerat, P., Naddef, D., Belenguer, J. M., Benavent, E., Corberan, A., & Rinaldi, G. (1995). Computational results with a branch and cut code for the capacitated vehicle routing problem.
Ayadi, R., & Benadada, Y. (2013). Memetic Algorithm for a Multi-Objective Vehicle Routing Problem with Multiple Trips. Int. J. Comput. Sci. Appl., 10(2), 72-91.
Azadeh, A., Elahi, S., Farahani, M. H., & Nasirian, B. (2017). A genetic algorithm-Taguchi based approach to inventory routing problem of a single perishable product with transshipment. Computers & Industrial Engineering, 104, 124-133.
Barkaoui, M., Berger, J., & Boukhtouta, A. (2015). Customer satisfaction in dynamic vehicle routing problem with time windows. Applied Soft Computing, 35, 423-432.
Berahhou, A., & Benadada, Y. (2020, October). Dynamic Vehicle Routing Problem with Simultaneous Delivery and Pickup: Formulation and Resolution. In 2020 5th International Conference on Logistics Operations Management (GOL) (pp. 1-8). IEEE.
Berbeglia, G., Cordeau, J. F., & Laporte, G. (2010). Dynamic pickup and delivery problems. European journal of operational research, 202(1), 8-15.
Bouanane, K., El Amrani, M., & Benadada, Y. (2020). The Vehicle Routing Problem with Simultaneous Delivery and Pickup: A taxonomic survey. DOI: 10.1504/IJLSM.2020.10036700.
Catay, B. (2010). A new saving-based ant algorithm for the vehicle routing problem with simultaneous pickup and delivery. Expert systems with applications, 37(10), 6809-6817.
Chang, M. S., Chen, S. R., & Hsueh, C. F. (2003). Real-time vehicle routing problem with time windows and simultaneous delivery/pickup demands. Journal of the Eastern Asia Society for Transportation Studies, 5, 2273-2286.
Chen, J. F., & Wu, T. H. (2006). Vehicle routing problem with simultaneous deliveries and pickups. Journal of the Operational Research Society, 57(5), 579-587.
Clarke, G., & Wright, J. W. (1964). Scheduling of vehicles from a central depot to a number of delivery points. Operations research, 12(4), 568-581.
Christopher, Y., Wahyuningsih, S., & Satyananda, D. (2021, May). Study of variable neighborhood descent and tabu search algorithm in VRPSDP. In Journal of Physics: Conference Series (Vol. 1872, No. 1, p. 012002). IOP Publishing.
Christofides, N. (1979). The vehicle routing problem. Combinatorial optimization.
Christofides, N., & Beasley, J. E. (1984). The period routing problem. Networks, 14(2), 237-256.
Dell’Amico, M., Righini, G., & Salani, M. (2006). A branch-and-price approach to the vehicle routing problem with simultaneous distribution and collection. Transportation science, 40(2), 235-247.
Dethloff, J. (2001). Vehicle routing and reverse logistics: the vehicle routing problem with simultaneous delivery and pick-up. OR-Spektrum, 23(1), 79-96.
Elhassania, M., Jaouad, B., & Ahmed, E. A. (2014, June). Solving the dynamic vehicle routing problem using genetic algorithms. In 2014 International Conference on Logistics Operations Management (pp. 62-69). IEEE.
Euchi, J., Yassine, A., & Chabchoub, H. (2015). The dynamic vehicle routing problem: Solution with hybrid metaheuristic approach. Swarm and Evolutionary Computation, 21, 41-53.
Fisher, M. L., & Jaikumar, R. (1981). A generalized assignment heuristic for vehicle routing. Networks, 11(2), 109-124.
Gajpal, Y., & Abad, P. (2009). An ant colony system (ACS) for vehicle routing problem with simultaneous delivery and pickup. Computers & Operations Research, 36(12), 3215-3223.
Gendreau, M., Guertin, F., Potvin, J. Y., & Séguin, R. (2006). Neighborhood search heuristics for a dynamic vehicle dispatching problem with pick-ups and deliveries. Transportation Research Part C: Emerging Technologies, 14(3), 157-174.
Goksal, F. P., Karaoglan, I., & Altiparmak, F. (2013). A hybrid discrete particle swarm optimization for vehicle routing problem with simultaneous pickup and delivery. Computers & industrial engineering, 65(1), 39-53.
Hanshar, F. T., & Ombuki-Berman, B. M. (2007). Dynamic vehicle routing using genetic algorithms. Applied Intelligence, 27(1), 89-99.
Holland, J.H. (1975). Adaptation in natural and artificial systems. Ann Arbor: University of Michigan Press.
Hong, L. (2012). An improved LNS algorithm for real-time vehicle routing problem with time windows. Computers & Operations Research, 39(2), 151-163.
Hu, Z. H., Sheu, J. B., Zhao, L., & Lu, C. C. (2015). A dynamic closed-loop vehicle routing problem with uncertainty and incompatible goods. Transportation Research Part C: Emerging Technologies, 55, 273-297.
Kalayci, C. B., & Kaya, C. (2016). An ant colony system empowered variable neighborhood search algorithm for the vehicle routing problem with simultaneous pickup and delivery. Expert Systems with Applications, 66, 163-175.
Khouadjia, M. R., Sarasola, B., Alba, E., Jourdan, L., & Talbi, E. G. (2012). A comparative study between dynamic adapted PSO and VNS for the vehicle routing problem with dynamic requests. Applied Soft Computing, 12(4), 1426-1439.
Kilby, P., Prosser, P., & Shaw, P. (1998). Dynamic VRPs: A study of scenarios. University of Strathclyde Technical Report, 1(11).
Lan, L., & Xia, W. (2015, October). Application based on PSO of hopfield neural network algorithm in dynamic VRPSPD. In 2015 IEEE 12th International Conference on e-Business Engineering (pp. 107-113). IEEE.
Li, J., Pardalos, P. M., Sun, H., Pei, J., & Zhang, Y. (2015). Iterated local search embedded adaptive neighborhood selection approach for the multi-depot vehicle routing problem with simultaneous deliveries and pickups. Expert Systems with Applications, 42(7), 3551-3561.
Liu, R., Xie, X., Augusto, V., & Rodriguez, C. (2013). Heuristic algorithms for a vehicle routing problem with simultaneous delivery and pickup and time windows in home health care. European Journal of Operational Research, 230(3), 475-486.
Luo, J. Y., Wang, J. Y., & Yu, H. (2011, August). A dynamic vehicle routing problem for medical supplies in large-scale emergencies. In 2011 6th IEEE Joint International Information Technology and Artificial Intelligence Conference (Vol. 1, pp. 271-275). IEEE.
Mańdziuk, J., & Żychowski, A. (2016). A memetic approach to vehicle routing problem with dynamic requests. Applied Soft Computing, 48, 522-534.
Mes, M., van der Heijden, M., & Schuur, P. (2010). Look-ahead strategies for dynamic pickup and delivery problems. OR spectrum, 32(2), 395-421.
Miller, B. L., & Goldberg, D. E. (1995). Genetic algorithms, tournament selection, and the effects of noise. Complex systems, 9(3), 193-212.
Min, H. (1989). The multiple vehicle routing problem with simultaneous delivery and pick-up points. Transportation Research Part A: General, 23(5), 377-386.
Mitrović-Minić, S., & Laporte, G. (2004). Waiting strategies for the dynamic pickup and delivery problem with time windows. Transportation Research Part B: Methodological, 38(7), 635-655.
Montemanni, R., Gambardella, L. M., Rizzoli, A. E., & Donati, A. V. (2005). Ant colony system for a dynamic vehicle routing problem. Journal of combinatorial optimization, 10(4), 327-343.
Moscato, P. (1989). On evolution, search, optimization, genetic algorithms and martial arts: Towards memetic algorithms. Caltech concurrent computation program, C3P Report, 826, 1989.
Necula, R., Breaban, M., & Raschip, M. (2017, June). Tackling dynamic vehicle routing problem with time windows by means of ant colony system. In 2017 IEEE Congress on Evolutionary Computation (CEC) (pp. 2480-2487). IEEE.
Ouaddi, K., Benadada, Y., & Mhada, F. Z. (2018). Ant colony system for dynamic vehicle routing problem with overtime. International Journal of Advanced Computer Science and Applications, 9(6), 306-315.
Ouaddi, K., Mhada, F., & Benadada, Y. (2020). Memetic algorithm for multi-tours dynamic vehicle routing problem with overtime (MDVRPOT). International Journal of Industrial Engineering Computations, 11(4), 643-662.
Pureza, V., & Laporte, G. (2008). Waiting and buffering strategies for the dynamic pickup and delivery problem with time windows. INFOR: Information Systems and Operational Research, 46(3), 165-175.
Rios, B. H. O., Xavier, E. C., Miyazawa, F. K., Amorim, P., Curcio, E., & Santos, M. J. (2021). Recent dynamic vehicle routing problems: A survey. Computers & Industrial Engineering, 160, 107604.
Ropke, S., & Pisinger, D. (2006). An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows. Transportation science, 40(4), 455-472.
Roy, R. K. (2010). A primer on the Taguchi method. Society of Manufacturing Engineers.
Sáez, D., Cortés, C. E., & Núñez, A. (2008). Hybrid adaptive predictive control for the multi-vehicle dynamic pick-up and delivery problem based on genetic algorithms and fuzzy clustering. Computers & Operations Research, 35(11), 3412-3438.
Sarbijan, M. S., & Behnamian, J. (2022). Multi-fleet feeder vehicle routing problem using hybrid metaheuristic. Computers & Operations Research, 105696.
Salhi, S., & Nagy, G. (1999). A cluster insertion heuristic for single and multiple depot vehicle routing problems with backhauling. Journal of the operational Research Society, 50(10), 1034-1042.
Schyns, M. (2015). An ant colony system for responsive dynamic vehicle routing. European Journal of Operational Research, 245(3), 704-718.
Sheridan, P. K., Gluck, E., Guan, Q., Pickles, T., Balcıog, B., & Benhabib, B. (2013). The dynamic nearest neighbor policy for the multi-vehicle pick-up and delivery problem. Transportation Research Part A: Policy and Practice, 49, 178-194.
Srour, F. J., Agatz, N., & Oppen, J. (2018). Strategies for handling temporal uncertainty in pickup and delivery problems with time windows. Transportation Science, 52(1), 3-19.
Subramanian, A., Cabral, L. D. A. F., & Carvalho, G. R. (2007, October). A hybrid metaheuristic for the vehicle routing problem with simultaneous pick-up and delivery. In ICIEOM: XIII international conference on industrial engineering and operations management, energy that moves production: A dialogue among integration, project and sustainability (pp. 09-11).
Subramanian, A., Drummond, L. M. D. A., Bentes, C., Ochi, L. S., & Farias, R. (2010). A parallel heuristic for the vehicle routing problem with simultaneous pickup and delivery. Computers & Operations Research, 37(11), 1899-1911.
Swihart, M. R., & Papastavrou, J. D. (1999). A stochastic and dynamic model for the single-vehicle pick-up and delivery problem. European Journal of Operational Research, 114(3), 447-464.
Taillard, É. (1993). Parallel iterative search methods for vehicle routing problems. Networks, 23(8), 661-673.
Tao, N., Shishasha, S., Peng, Z., & Tao, G. (2021). Disruption management decision model for VRPSDP under changes of customer distribution demand. Journal of Ambient Intelligence and Humanized Computing, 12(2), 2053-2063.
Zachariadis, E. E., Tarantilis, C. D., & Kiranoudis, C. T. (2010). An adaptive memory methodology for the vehicle routing problem with simultaneous pick-ups and deliveries. European Journal of Operational Research, 202(2), 401-411.
Zhao, L., Liang, X., & Yang, H. (2018, June). Disruption management model for VRPSDP with new customer request for pickup. In 2018 Chinese Control And Decision Conference (CCDC) (pp. 423-427). IEEE.
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Journal: International Journal of Industrial Engineering Computations | Year: 2022 | Volume: 13 | Issue: 4 | Views: 1728 | Reviews: 0

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