How to cite this paper
Zhang, X., Chen, S., Cao, Q & Ren, X. (2023). Optimization of emergency supplies paths based on dynamic real-time split delivery.International Journal of Industrial Engineering Computations , 14(4), 623-644.
Refrences
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Bianchessi, N., & Irnich, S. (2019). Branch-and-cut for the split delivery vehicle routing problem with time windows. Transportation Science, 53(2), 442-462.
Bianchessi, N., Drexl, M., & Irnich, S. (2019). The split delivery vehicle routing problem with time windows and customer inconvenience constraints. Transportation Science, 53(4), 1067-1084.
Bortfeldt, A., & Yi, J. M. (2020). The split delivery vehicle routing problem with three-dimensional loading constraints. European Journal of Operational Research, 282(2), 545-558.
Cheikh, M., & Loukil, T. M. (2023). A general variable neighbourhood search for the commodity constrained split delivery vehicle routing problem. International Journal of Logistics Systems and Management, 45(2), 249-267.
Chen, F., Ding, W. L., Ye, Y. P., & Wang, H. (2020). Optimal coordination model of medical commodities in the initial stage of the outbreak of public health events. China Journal of Highway and Transport, 33(11), 65-72.
Comert, S. E., & Yazgan, H. R. (2023). A new approach based on hybrid ant colony optimization-artificial bee colony algorithm for multi-objective electric vehicle routing problems. Engineering Applications of Artificial Intelligence, 123, 106375.
Dinh, N. M., Archetti, C., & Bertazzi, L. (2023). The inventory routing problem with split deliveries. Networks. https://doi.org/10.1002/net.22175
Djimesah, I. E., Okine, A. N. D., & Mireku, K. K. (2018). Influential factors in creating warning systems towards flood disaster management in Ghana: An analysis of 2007 Northern flood. International Journal of Disaster Risk Reduction, 28, 318-326.
Dorigo, M., & Gambardella, L.M. (1997). Ant colony system: a cooperative learning approach to the traveling salesman problem. IEEE Transactions on Evolutionary Computation,1(1), 53–56.
Dror, M., & Trudeau, P. (1989). Savings by split delivery routing. Transportation Science, 23(2), 141-145.
Dubey, N., & Tanksale, A. (2023). A multi-depot vehicle routing problem with time windows, split pickup and split delivery for surplus food recovery and redistribution. Expert Systems with Applications, 120807. https://doi.org/10.1016/j.eswa.2023.120807
Eydi, A., & Alavi, H. (2019). Vehicle routing problem in reverse logistics with split demands of customers and fuel consumption optimization. Arabian Journal for Science and Engineering, 44, 2641-2651.
Gribkovskaia, I., Halskau sr, Ø., Laporte, G., & Vlček, M. (2007). General solutions to the single vehicle routing problem with pickups and deliveries. European Journal of Operational Research, 180(2), 568-584.
Haddad, M. N., Martinelli, R., Vidal, T., Martins, S., Ochi, L. S., Souza, M. J. F., & Hartl, R. (2018). Large neighborhood-based metaheuristic and branch-and-price for the pickup and delivery problem with split loads. European Journal of Operational Research, 270(3), 1014-1027.
Han, A. F. W., & Chu, Y. C. (2016). A multi-start heuristic approach for the split-delivery vehicle routing problem with minimum delivery amounts. Transportation Research Part E: Logistics and Transportation Review, 88, 11-31.
Han, M. X., Du, Z. F., Zhu, H. T., Li, Y. C., Yuan, Q. Y., & Zhu, H. M. (2022). Golden-Sine dynamic marine predator algorithm for addressing engineering design optimization. Expert Systems with Applications, 210, 118460.
Hidayat, Y. A., Stephia, A. G., Yudhistira, T., & Zamal, M. A. (2022). Warehouse location determination and route optimization for an upcoming 5 MWp photovoltaic solar panels in central Borneo Indonesia. Journal of the eastern Asia society for transport studies, 14, 1316-1333.
Holguín-Veras, J., Pérez, N., Jaller, M., Van Wassenhove, L. N., & Aros-Vera, F. (2013). On the appropriate objective function for post-disaster humanitarian logistics models. Journal of Operations Management, 31(5), 262-280.
Ji, B., Zhou, S. Q., Samson, S. Y., & Wu, G. H. (2021). An enhanced neighborhood search algorithm for solving the split delivery vehicle routing problem with two-dimensional loading constraints. Computers & Industrial Engineering, 162, 107720.
Liu, H. S., Sun, Y. X., Pan, N., Li, Y., An, Y. Q., & Pan, D. L. (2022). Study on the optimization of urban emergency supplies distribution paths for epidemic outbreaks. Computers & Operations Research, 146, 105912.
Lu, Y. C., Yang, C., & Yang, J. (2022). A multi-objective humanitarian pickup and delivery vehicle routing problem with drones. Annals of Operations Research, 319(1), 291-353.
Luo, J., Shi, L., Xue, R., & El-baz, D. (2023). Optimization models and solving approaches in relief distribution concerning victims' satisfaction: A review. Applied Soft Computing, 110398. https://doi.org/10.1016/j.asoc.2023.110398
Mason, D. J., & Friese, C. R. (2020). Protecting health care workers against COVID-19—and being prepared for future pandemics. JAMA Health Forum, 1(3), e200353.
McNabb, M. E., Weir, J. D., Hill, R. R., & Hall, S. N. (2015). Testing local search move operators on the vehicle routing problem with split deliveries and time windows. Computers & Operations Research, 56, 93-109.
Ni, W., Shu, J., & Song, M. (2018). Location and emergency inventory pre‐positioning for disaster response operations: Min‐max robust model and a case study of Yushu earthquake. Production and Operations Management, 27(1), 160-183.
Peng, Z. X., Wang, C., Xu, W. Q., & Zhang, J. S. (2022). Research on location-routing problem of maritime emergency materials distribution based on bi-level programming. Mathematics, 10(8), 1243.
Ren, T., Luo, T. Y., Jia, B. B., Yang, B. H., Wang, L., & Xing, L. N. (2023). Improved ant colony optimization for the vehicle routing problem with split pickup and split delivery. Swarm and Evolutionary Computation, 77, 101228.
Ren, X. Y., Chen, S., & Ren, L. Y. (2023). Optimization of regional emergency supplies distribution vehicle route with dynamic real-time demand. Mathematical biosciences and engineering: MBE, 20(4), 7487-7518.
Ren, X. Y., Chen, S., Wang, K. Y., & Tan, J. (2022). Design and application of improved sparrow search algorithm based on sine cosine and firefly perturbation. Mathematical Biosciences and Engineering: MBE, 19(11), 11422-11452.
Sentia, P. D., Abdul Shukor, S., Wahab, A. N. A., & Mukhtar, M. (2023). Logistic distribution in humanitarian supply chain management: a thematic literature review and future research. Annals of Operations Research, 323(1-2), 175-201.
Solomon, M. M. (1987). Algorithms for the vehicle routing and scheduling problems with time window constraints. Operations research, 35(2), 254–265.
Song, Y. H., Huang, X., Ma, Y. P., & Li, M. X. (2021). Emergency resource allocation considering psychological pain effect of disaster victims under multi-dimensional fairness measurement. Journal of Safety Science and Technology, 17(4), 47-53.
Useche, S. A., Ortiz, V. G., & Cendales, B. E. (2017). Stress-related psychosocial factors at work, fatigue, and risky driving behavior in bus rapid transport (BRT) drivers. Accident Analysis & Prevention, 104, 106-114.
Wan, M. R., Ye, C. M., & Peng, D. J. (2023). Multi-period dynamic multi-objective emergency material distribution model under uncertain demand. Engineering Applications of Artificial Intelligence, 117, 105530.
Wang, S. L., & Sun, B. Q. (2023). Model of multi-period emergency material allocation for large-scale sudden natural disasters in humanitarian logistics: Efficiency, effectiveness and equity. International Journal of Disaster Risk Reduction, 85, 103530.
Wang, X. P., Ma, C., & Ruan, J. H. (2013). Emergency supplies optimal scheduling considering the public's psychological risk perception. Systems Engineering-Theory & Practice, 33(7), 1735-1742.
Wu, H. F., Chen, X. Q., Mao, Q. H., Zhang, Q. N., & Zhang, S, C. (2013). Improved ant colony algorithm based on natural selection strategy for solving TSP problem. Journal on Communications, 34(4), 165-170.
Yu, L., Zhang, C. R., Yang, H. S., & Miao, L. X. (2018). Novel methods for resource allocation in humanitarian logistics considering human suffering. Computers & Industrial Engineering, 119, 1-20.
Yu, Y., Gao, S. C., Cheng, S., Wang, Y. R., Song, S. Y., & Yuan, F. G. (2018). CBSO: a memetic brain storm optimization with chaotic local search. Memetic Computing, 10, 353-367.
Zhang, D. Z., Zhang, Y. R., Li, S. L., Li, S. Y., & Chen, W. R. (2023). Bi-objective robust optimisation on relief collaborative distribution considering secondary disasters. International Journal of Production Research, 1-20. https://doi.org/10.1080/00207543.2023.2217306
Zhong, Y. Z. (2021). A flood disaster relief emergency material distribution strategy based on people’s psychological perception. Arabian Journal of Geosciences, 14(10), 1-9.
Bianchessi, N., & Irnich, S. (2019). Branch-and-cut for the split delivery vehicle routing problem with time windows. Transportation Science, 53(2), 442-462.
Bianchessi, N., Drexl, M., & Irnich, S. (2019). The split delivery vehicle routing problem with time windows and customer inconvenience constraints. Transportation Science, 53(4), 1067-1084.
Bortfeldt, A., & Yi, J. M. (2020). The split delivery vehicle routing problem with three-dimensional loading constraints. European Journal of Operational Research, 282(2), 545-558.
Cheikh, M., & Loukil, T. M. (2023). A general variable neighbourhood search for the commodity constrained split delivery vehicle routing problem. International Journal of Logistics Systems and Management, 45(2), 249-267.
Chen, F., Ding, W. L., Ye, Y. P., & Wang, H. (2020). Optimal coordination model of medical commodities in the initial stage of the outbreak of public health events. China Journal of Highway and Transport, 33(11), 65-72.
Comert, S. E., & Yazgan, H. R. (2023). A new approach based on hybrid ant colony optimization-artificial bee colony algorithm for multi-objective electric vehicle routing problems. Engineering Applications of Artificial Intelligence, 123, 106375.
Dinh, N. M., Archetti, C., & Bertazzi, L. (2023). The inventory routing problem with split deliveries. Networks. https://doi.org/10.1002/net.22175
Djimesah, I. E., Okine, A. N. D., & Mireku, K. K. (2018). Influential factors in creating warning systems towards flood disaster management in Ghana: An analysis of 2007 Northern flood. International Journal of Disaster Risk Reduction, 28, 318-326.
Dorigo, M., & Gambardella, L.M. (1997). Ant colony system: a cooperative learning approach to the traveling salesman problem. IEEE Transactions on Evolutionary Computation,1(1), 53–56.
Dror, M., & Trudeau, P. (1989). Savings by split delivery routing. Transportation Science, 23(2), 141-145.
Dubey, N., & Tanksale, A. (2023). A multi-depot vehicle routing problem with time windows, split pickup and split delivery for surplus food recovery and redistribution. Expert Systems with Applications, 120807. https://doi.org/10.1016/j.eswa.2023.120807
Eydi, A., & Alavi, H. (2019). Vehicle routing problem in reverse logistics with split demands of customers and fuel consumption optimization. Arabian Journal for Science and Engineering, 44, 2641-2651.
Gribkovskaia, I., Halskau sr, Ø., Laporte, G., & Vlček, M. (2007). General solutions to the single vehicle routing problem with pickups and deliveries. European Journal of Operational Research, 180(2), 568-584.
Haddad, M. N., Martinelli, R., Vidal, T., Martins, S., Ochi, L. S., Souza, M. J. F., & Hartl, R. (2018). Large neighborhood-based metaheuristic and branch-and-price for the pickup and delivery problem with split loads. European Journal of Operational Research, 270(3), 1014-1027.
Han, A. F. W., & Chu, Y. C. (2016). A multi-start heuristic approach for the split-delivery vehicle routing problem with minimum delivery amounts. Transportation Research Part E: Logistics and Transportation Review, 88, 11-31.
Han, M. X., Du, Z. F., Zhu, H. T., Li, Y. C., Yuan, Q. Y., & Zhu, H. M. (2022). Golden-Sine dynamic marine predator algorithm for addressing engineering design optimization. Expert Systems with Applications, 210, 118460.
Hidayat, Y. A., Stephia, A. G., Yudhistira, T., & Zamal, M. A. (2022). Warehouse location determination and route optimization for an upcoming 5 MWp photovoltaic solar panels in central Borneo Indonesia. Journal of the eastern Asia society for transport studies, 14, 1316-1333.
Holguín-Veras, J., Pérez, N., Jaller, M., Van Wassenhove, L. N., & Aros-Vera, F. (2013). On the appropriate objective function for post-disaster humanitarian logistics models. Journal of Operations Management, 31(5), 262-280.
Ji, B., Zhou, S. Q., Samson, S. Y., & Wu, G. H. (2021). An enhanced neighborhood search algorithm for solving the split delivery vehicle routing problem with two-dimensional loading constraints. Computers & Industrial Engineering, 162, 107720.
Liu, H. S., Sun, Y. X., Pan, N., Li, Y., An, Y. Q., & Pan, D. L. (2022). Study on the optimization of urban emergency supplies distribution paths for epidemic outbreaks. Computers & Operations Research, 146, 105912.
Lu, Y. C., Yang, C., & Yang, J. (2022). A multi-objective humanitarian pickup and delivery vehicle routing problem with drones. Annals of Operations Research, 319(1), 291-353.
Luo, J., Shi, L., Xue, R., & El-baz, D. (2023). Optimization models and solving approaches in relief distribution concerning victims' satisfaction: A review. Applied Soft Computing, 110398. https://doi.org/10.1016/j.asoc.2023.110398
Mason, D. J., & Friese, C. R. (2020). Protecting health care workers against COVID-19—and being prepared for future pandemics. JAMA Health Forum, 1(3), e200353.
McNabb, M. E., Weir, J. D., Hill, R. R., & Hall, S. N. (2015). Testing local search move operators on the vehicle routing problem with split deliveries and time windows. Computers & Operations Research, 56, 93-109.
Ni, W., Shu, J., & Song, M. (2018). Location and emergency inventory pre‐positioning for disaster response operations: Min‐max robust model and a case study of Yushu earthquake. Production and Operations Management, 27(1), 160-183.
Peng, Z. X., Wang, C., Xu, W. Q., & Zhang, J. S. (2022). Research on location-routing problem of maritime emergency materials distribution based on bi-level programming. Mathematics, 10(8), 1243.
Ren, T., Luo, T. Y., Jia, B. B., Yang, B. H., Wang, L., & Xing, L. N. (2023). Improved ant colony optimization for the vehicle routing problem with split pickup and split delivery. Swarm and Evolutionary Computation, 77, 101228.
Ren, X. Y., Chen, S., & Ren, L. Y. (2023). Optimization of regional emergency supplies distribution vehicle route with dynamic real-time demand. Mathematical biosciences and engineering: MBE, 20(4), 7487-7518.
Ren, X. Y., Chen, S., Wang, K. Y., & Tan, J. (2022). Design and application of improved sparrow search algorithm based on sine cosine and firefly perturbation. Mathematical Biosciences and Engineering: MBE, 19(11), 11422-11452.
Sentia, P. D., Abdul Shukor, S., Wahab, A. N. A., & Mukhtar, M. (2023). Logistic distribution in humanitarian supply chain management: a thematic literature review and future research. Annals of Operations Research, 323(1-2), 175-201.
Solomon, M. M. (1987). Algorithms for the vehicle routing and scheduling problems with time window constraints. Operations research, 35(2), 254–265.
Song, Y. H., Huang, X., Ma, Y. P., & Li, M. X. (2021). Emergency resource allocation considering psychological pain effect of disaster victims under multi-dimensional fairness measurement. Journal of Safety Science and Technology, 17(4), 47-53.
Useche, S. A., Ortiz, V. G., & Cendales, B. E. (2017). Stress-related psychosocial factors at work, fatigue, and risky driving behavior in bus rapid transport (BRT) drivers. Accident Analysis & Prevention, 104, 106-114.
Wan, M. R., Ye, C. M., & Peng, D. J. (2023). Multi-period dynamic multi-objective emergency material distribution model under uncertain demand. Engineering Applications of Artificial Intelligence, 117, 105530.
Wang, S. L., & Sun, B. Q. (2023). Model of multi-period emergency material allocation for large-scale sudden natural disasters in humanitarian logistics: Efficiency, effectiveness and equity. International Journal of Disaster Risk Reduction, 85, 103530.
Wang, X. P., Ma, C., & Ruan, J. H. (2013). Emergency supplies optimal scheduling considering the public's psychological risk perception. Systems Engineering-Theory & Practice, 33(7), 1735-1742.
Wu, H. F., Chen, X. Q., Mao, Q. H., Zhang, Q. N., & Zhang, S, C. (2013). Improved ant colony algorithm based on natural selection strategy for solving TSP problem. Journal on Communications, 34(4), 165-170.
Yu, L., Zhang, C. R., Yang, H. S., & Miao, L. X. (2018). Novel methods for resource allocation in humanitarian logistics considering human suffering. Computers & Industrial Engineering, 119, 1-20.
Yu, Y., Gao, S. C., Cheng, S., Wang, Y. R., Song, S. Y., & Yuan, F. G. (2018). CBSO: a memetic brain storm optimization with chaotic local search. Memetic Computing, 10, 353-367.
Zhang, D. Z., Zhang, Y. R., Li, S. L., Li, S. Y., & Chen, W. R. (2023). Bi-objective robust optimisation on relief collaborative distribution considering secondary disasters. International Journal of Production Research, 1-20. https://doi.org/10.1080/00207543.2023.2217306
Zhong, Y. Z. (2021). A flood disaster relief emergency material distribution strategy based on people’s psychological perception. Arabian Journal of Geosciences, 14(10), 1-9.