A systematic review of multi-depot vehicle routing problems
Main Article Content
Abstract
Multi-Depot Vehicle Routing Problem (MDVRP) is a heuristic optimization problem that capture interest of several researchers' for its applicability to real-life situations. The variant of MDVRP are solved with some certain constraints such as service time, time window, vehicle capacity, travelled distance etc. these makes MDVRP to cover several situations In this, 76 studies related to MDVRP from 2012 to 2022 were systematically reviewed. The studies are review based on their constraints and an application through various fields. The goal of this research is to examine the contemporary state of MDVRP and its applications. To achieve this goal, we formed a comprehensive search process which was employed on high rated scientific journals databases. The search process resulted to numerous important research papers in the research domain which were theoretically reviewed. The research papers found are screened based on the titled, abstract, year of publication and exhaustive reading of full text in order to extract the related information that will address the aim of this study. Finally, the selected studies were categorized based on constraints and real-life applications they tackled. The outcome of our study shows that minimizing travelled distance and service time were the most constraints addressed by the selected studies, transportation network, waste management; distribution problems were the most widely used real-life applications of MDVRP concentrated on.
Metrics
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Azadeh, A., and Farrokhi, H. (2017). The close - open mixed multi-depot vehicle Routing Problem considering internal and external fleet. international journal of transportation research. DOI: https://doi.org/10.1080/19427867.2016.1274468
Brandão, J. (2020). A memory-based iterated local search algorithm for the multi-depot open vehicle routing problem. European Journal of Operational Research, 559–571, https://doi.org/10.1016/j.ejor.2020.01.008. DOI: https://doi.org/10.1016/j.ejor.2020.01.008
Carise, E. S., Arinei C.L.S., Darvish, M. and Leandro, C.C. (2022). Delivery in conjested urvan environment: the benefits of several depots and deverse fleets. CIRRELT , 1-31.
Chiu SW., Chen S-W.,Chang C-K., Chiu Y. SP. (2016). Optimization of a Multi–Product Intra-Supply Chain System with Failure in Rework. Open Access Journal, 1-17, DOI:10.1371.
Contardo, C., and Martinelli R. (2014). A new exact algorithm for the multi-depot vehicle routing problem under capacity and route length constraints. Discrete Optimization, 129–146. DOI: https://doi.org/10.1016/j.disopt.2014.03.001
Elmidaoui, M., Mohammed, M., and Khalifa, M. (2020). A novel Approach of smart logistics for the Heath-Care Sector Using Genetic Algorithm. Advances in Science, Technology and Engineering , 1143-1152. DOI: https://doi.org/10.25046/aj0506138
Emir, Z., zenana, Ð., and Emir, B. (2020). An Adaptive Data-Driven Approach to Solve Real-World Vehicle Routing Problems in Logistics. Hindawi Complexity, 1-24, https://doi.org/10.1155/2020/7386701. DOI: https://doi.org/10.1155/2020/7386701
Emrah, D., Tolga, B., and Gilbert, L. (2014). The bi-objective pollution-routing problem. European Journal of Operational Research, 464-478. DOI: https://doi.org/10.1016/j.ejor.2013.08.002
Fitriana, R., Moengin, P., and Kusumaningrum, U. (2019). Improvement Route for Distribution Solutions MDVRP (Multi Depot Vehicle Routing Problem) using Genetic Algorithm. IOP Conf. Series: Materials Science and Engineering, 1-8, doi:10.1088/1757-899X/528/1/012042. DOI: https://doi.org/10.1088/1757-899X/528/1/012042
Ganepola, D., Jayarathna, N. D., & Madhushani, G. (2018). An intelligent cost optimized central warehouse and redistribution root plan with truck allocation system in Colombo region for Lion Brewery Ceylon PLC. . Journal of Sustainable Development of Transport and Logistics, 66-73. DOI: https://doi.org/10.14254/jsdtl.2018.3-2.4
Hou, D., Fan, H. and Ren X. (2021. Time Dependant Multi Depot Heterogeneous Vehicle Routing Problem considering temporal spatial distance. Published by Sustainability vol.13(9), 4674. DOI: https://doi.org/10.3390/su13094674
Jayarathna, D. G. N. D., Lanel, G. H. J., & Juman, Z. A. M. S. (2021). Survey on Ten Years of Multi-Depot Vehicle Routing Problems: Mathematical Models, Solution Methods and Real-Life Applications. Published by IDEAS SPREAD (sustainable development research) . DOI: https://doi.org/10.30560/sdr.v3n1p36
Jayarathna, N., Lanel, J., and Juman Z.A.M.S. . (2020). Five years of multi-depot vehicle routing problems . Journal of Sustainable Development of Transport and Logistics, 109-123. DOI: https://doi.org/10.14254/jsdtl.2020.5-2.10
karakatic, S., and podgorelec, V., (2014). A survey genetic Algorithm for solving MDVRP. J. Application and soft computing. Elsevier .
Kramer, R., Cordeau, J. F., & Iori, M. (2019). Rich vehicle routing with auxiliary depots and anticipated deliveries: An application to pharmaceutical distribution. Transportation Research Part E: Logistics and Transportation Review, 162-174. DOI: https://doi.org/10.1016/j.tre.2019.07.012
Kitchenham, B., and Charters, S. (2007) Guideline for performing Systematic Literature Reviews in Software Engineering, Technical Reports EBSE 2007-00, Keele University and Durham university Joint report.
Luis, F. G., Eliana, M. T. and Ramón, A. G. . (2018). Multi-objective MDVRP solution considering route balance and cost using the ILS metaheuristic. International Journal of Industrial Engineering Computations, 33-46. DOI: https://doi.org/10.5267/j.ijiec.2017.5.002
Mancini S. (2016). A real Life Multi Depot Multi Period Vehicle Routing Problem with hetrogeneous fleet: formulation and adaptive large neighbourhood search based metaheuristics. Transportation Research Part C : Emarging Technologies, 100-112. DOI: https://doi.org/10.1016/j.trc.2015.06.016
Mandeep, K., and Shanky, G. . (2013). Application of ACO to Disentangle Max-Min MDVRP Using Clustering Technique . International Journal of Scientific and Research Publications, 1-6.
Meesuptaweekoon, k., and chaovalitwongse, P. (2014). Dynamic Vehicle Routing Problem with Multiple Depots(D-MDVRP). Enginnering journal, vol. 18 issue 4, ISSN 0125-8281, (http://www.engj.org/) DOI: https://doi.org/10.4186/ej.2014.18.4.135
Moher, D., Liberti, A., Tetzlaff, J., Altman, D. (2009). Preffered reporting items for systematic reviews and meta-analysis: The PRISMA Statement.BMJ 2009:339:b2535 https://doi.org/101136/bmj.b2535, published July 2009. DOI: https://doi.org/10.1136/bmj.b2535
Montoya-Torres, JR., Franco, JL., Isaza, SN., Jimenez, HF., and Herazo-padilla (2015). Literature review on the Vehicle Routing Problem with Multiple Depots. Computers and Industrial Engineering,79 , 115-129. DOI: https://doi.org/10.1016/j.cie.2014.10.029
Moonsri, K., Sethanan, K., Worasan, K. (2022). A Novel Enhanced Differential Evolution Algorithm for Outbound Logistics of the Poultry Industry in Thailand. Journal of Open Innovations: technology, market and complexity, 1-19. DOI: https://doi.org/10.3390/joitmc8010015
Sangeet, A., and Sonia, S. (2015). SIMULTANEOUSLY PICKUP AND DELIVERY MDVRP WITH MULTI OBJECTIVE G.A . International Journal of Computer Application, 190-195.
Serrano-Hernandez, A., de la Torre, R., Cadarso, L., Faulin, J. . (2021). Urban e-Grocery Distribution Design in Pamplona (Spain) Applying an Agent-Based Simulation Model with Horizontal Cooperation Scenarios. Algorithms, https://doi.org/10.3390/a14010020, 1-22. DOI: https://doi.org/10.3390/a14010020
Oliveira, F.B., Enayatifar, R., Sadaei, H.J., Guimaraes, F.G., Potvin, J.Y. (2015, Sepptember 5). A cooperative coevolutionary algorithm for the Multi-Depot Vehicle Routing Problem. Elsavier, 1-14.
Osaba, E., Yang, X. S., Fister, I., Del Ser, J., Lopez-Garcia, P., & Vazquez-Pardavila, A. J. A. . (2019). Discrete and Improved Bat Algorithm for solving a medical goods distribution problem with pharmacological waste collection. Swarm and Evolutionary Computation, 273-286, https://doi.org/10.1016/j.swevo.2018.04.001. DOI: https://doi.org/10.1016/j.swevo.2018.04.001
Osaba, E., Yang, X.-S., Diaz, F., Onieva, E., Masegosa, A. D., & Perallos, A. (2017). A Discrete Firefly Algorithm to Solve a Rich Vehicle Routing Problem Modelling a Newspaper Distribution System with Recycling Policy. Soft Computing, 5295–5308, soft computing. DOI: https://doi.org/10.1007/s00500-016-2114-1
Soto, M., Sevaux, M., Rossi, A., & Reinholz, A. (2017). Multiple neighborhood search, tabu search and ejection chains for the multi-depot open vehicle routing problem. Computers & Industrial Engineering, 211–222. DOI: https://doi.org/10.1016/j.cie.2017.03.022
Stodola, P., and Mazal J. (2015). The Tactical Model based on a Multi-Depot Vehicle Routing Problem . New Developments in Pure and Applied Mathematics, 196-201.
Syed, T. Z., Zahrul, J. P., and Firoz Mahmud . (2012). A Novel Three-Phase Approach for Solving Multi-Depot Vehicle Routing Problem with Stochastic Demand . Algorithms Research, 15-19.
Tang, Y. (2016). An Improved Ant Colony Optimization for Multi-Depot Vehicle Routing Problem. International Journal of Engineering and Technology, 385-388. DOI: https://doi.org/10.7763/IJET.2016.V8.918
Tingxi, W., Zhongnan Z., Kelvin K. L. W. (2016). Multi-Objective AlgorithmforBloodSupply viaUnmannedAerialVehiclestothe WoundedinanEmergencySituation. Open Access, 1-22.
Tohidifard, M., Tavakkoli-Moghaddam, R., Navazi, F., & Partovi, M. (2018). A Multi-Depot Home Care Routing Problem with Time Windows and Fuzzy Demands Solving by Particle Swarm Optimization and Genetic Algorithm. Science Direct, 358-363, https://doi.org/10.1016/j.ifacol.2018.08.318. DOI: https://doi.org/10.1016/j.ifacol.2018.08.318
Wei, T., Zhixiang, F., Qungquan, L., Shih-lung, S., and BiYu, C. (2014). A bi - level voronoi diagram-based metaheuristic for large-scale Multi-depot Vehicle Routing Problem. Transportation Research Part E, Elsevier, 84-97. DOI: https://doi.org/10.1016/j.tre.2013.11.003
Yadong, Y., Haiping Ma., Mei, Yu., Sengang, Y. and Xiaolei, C. (2018). Multipopulation Management in Evolutionary Algorithms and Application to Complex Warehouse Scheduling Problems. Hindawi Complexity, 1-14, https://doi.org/10.1155/2018/4730957. DOI: https://doi.org/10.1155/2018/4730957
Yang, J., Zhou L, Liu H. (2021). Hybrid genetic algorithm-based optimisation of the batch order picking in a dense mobile rack warehouse. Open Access, 1-25. DOI: https://doi.org/10.1371/journal.pone.0249543
Yanjun, S., Lingling, L., Fanyi, H., and Qiaomei, H. . (2020). A Heuristic Solution Method for Multi-Depot Vehicle Routing-Based Waste Collection Problems. Applied Science, Appl. Sci., 10, 2403, 1-17; doi:10.3390/app10072403 www.mdpi.com/journal/applsci. DOI: https://doi.org/10.3390/app10072403
Yiyo, K., and Chi-Chang, W. (2012). A variable neighbourhood search for Multi-Depot Vehicle Routing Problem with loading cost. Elservia, 6949–6954. DOI: https://doi.org/10.1016/j.eswa.2012.01.024
Yong, W., Lingyu, R.,1 Xiangyang G., and Yajie, Z. (2021). Multi-Depot Pickup and Delivery Problem with Resource Sharing. Hindawi Journal of Advanced Transportation, 1-22. DOI: https://doi.org/10.1155/2021/5182989
Zhang, W., Gajpal, Y., Srimantoorao, S., and Wei, Q. (2020). Multi- Depot Green Vehicle Routing Problem to minimize Carbon Emission. Sustainability, 1-19, www.mdpi.com/journal/sustainability. DOI: https://doi.org/10.3390/su12083500