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.
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.