research-article

An adaptive large neighborhood search for the multi-depot dynamic vehicle routing problem with time windows

Authors:

Min HuangAuthors Info & Claims

Volume 191, Issue C

https://doi.org/10.1016/j.cie.2024.110122

Published: 18 July 2024 Publication History

Highlights

•

We identified dynamic MD-VRP as a multi-period multi-depot mixed fleet MD-VRP.

•

An ALNS that embeds novel removal and insertion operators is developed.

•

Some insights are provided after the computational tests.

Abstract

As part of this study, we examine the multi-depot dynamic vehicle routing problem with time windows (MD-DVRPTW), in which customer requests emerge stochastically throughout the operational horizon. To provide timely and comprehensive service to these customers, a re-optimization framework utilizing an adaptive large neighborhood search (ALNS) has been developed. In our ALNS algorithm, two novel removal operators and a time window compatibility-based insertion method are proposed to improve its accuracy and efficiency. This study demonstrates that our ALNS is well-suited for dynamic problems that require re-optimization within a very short period compared to state-of-the-art algorithms. While conducting benefit analyses for MD-DVRPTW, we illustrate that the fixed cost of the vehicle can also impact route planning. Furthermore, accelerating responsiveness does not necessarily improve dynamic problems; instead, it may increase costs.

References

[1]

A.M.F. AbdAllah, D.L. Essam, R.A. Sarker, On solving periodic re-optimization dynamic vehicle routing problems, Applied Soft Computing 55 (2017) 1–12,.

Digital Library

[2]

M. Alinaghian, N. Shokouhi, Multi-depot multi-compartment vehicle routing problem, solved by a hybrid adaptive large neighborhood search, Omega 76 (2018) 85–99.

[3]

W.K. Anuar, L.S. Lee, H.-V. Seow, S. Pickl, A multi-depot dynamic vehicle routing problem with stochastic road capacity: An mdp model and dynamic policy for post-decision state rollout algorithm in reinforcement learning, Mathematics 10 (15) (2022) 2699,.

[4]

C. Archetti, F. Guerriero, G. Macrina, The online vehicle routing problem with occasional drivers, Computers & Operations Research 127 (2021),.

[5]

N. Azi, M. Gendreau, J.-Y. Potvin, An adaptive large neighborhood search for a vehicle routing problem with multiple routes, Computers & Operations Research 41 (2014) 167–173,.

Digital Library

[6]

T. Bektaş, L. Gouveia, D. Santos, Compact formulations for multi-depot routing problems: Theoretical and computational comparisons, Computers & Operations Research 124 (2020),.

[7]

T. Bektaş, P.P. Repoussis, C.D. Tarantilis, Chapter 11: Dynamic vehicle routing problems, in: Vehicle Routing: Problems, Methods, and Applications, Second Edition, SIAM, 2014, pp. 299–347.

[8]

D.J. Bertsimas, G. Van Ryzin, A stochastic and dynamic vehicle routing problem in the Euclidean plane, Operations Research 39 (4) (1991) 601–615,.

Digital Library

[9]

K. Braekers, K. Ramaekers, I. Van Nieuwenhuyse, The vehicle routing problem: State of the art classification and review, Computers & Industrial Engineering 99 (2016) 300–313.

Digital Library

[10]

J. Brandão, A memory-based iterated local search algorithm for the multi-depot open vehicle routing problem, European Journal of Operational Research 284 (2) (2020) 559–571.

[11]

L. Cai, X. Wang, Z. Luo, Y. Liang, A hybrid adaptive large neighborhood search and tabu search algorithm for the electric vehicle relocation problem, Computers & Industrial Engineering 167 (2022),.

Digital Library

[12]

S. Chen, R. Chen, G.-G. Wang, J. Gao, A.K. Sangaiah, An adaptive large neighborhood search heuristic for dynamic vehicle routing problems, Computers & Electrical Engineering 67 (2018) 596–607,.

Digital Library

[13]

Z.-L. Chen, H. Xu, Dynamic column generation for dynamic vehicle routing with time windows, Transportation Science 40 (1) (2006) 74–88,.

Digital Library

[14]

J.-F. Cordeau, G. Laporte, A. Mercier, A unified tabu search heuristic for vehicle routing problems with time windows, Journal of the Operational Research Society 52 (8) (2001) 928–936,.

[15]

G.B. Dantzig, J.H. Ramser, The truck dispatching problem, Management Science 6 (1) (1959) 80–91,.

Digital Library

[16]

E. Demir, T. Bektaş, G. Laporte, An adaptive large neighborhood search heuristic for the pollution-routing problem, European Journal of Operational Research 223 (2) (2012) 346–359,.

[17]

H. Diefenbach, S. Emde, C.H. Glock, Multi-depot electric vehicle scheduling in in-plant production logistics considering non-linear charging models, European Journal of Operational Research 306 (2) (2023) 828–848,.

[18]

H. Fan, Y. Zhang, P. Tian, Y. Lv, H. Fan, Time-dependent multi-depot green vehicle routing problem with time windows considering temporal-spatial distance, Computers & Operations Research 129 (2021),.

[19]

K. Gkiotsalitis, C. Iliopoulou, K. Kepaptsoglou, An exact approach for the multi-depot electric bus scheduling problem with time windows, European Journal of Operational Research 306 (1) (2023) 189–206,.

[20]

F.D. Hildebrandt, B.W. Thomas, M.W. Ulmer, Opportunities for reinforcement learning in stochastic dynamic vehicle routing, Computers & Operations Research 106071 (2022).

[21]

E. Jabir, V.V. Panicker, R. Sridharan, Design and development of a hybrid ant colony-variable neighbourhood search algorithm for a multi-depot green vehicle routing problem, Transportation Research Part D: Transport and Environment 57 (2017) 422–457,.

[22]

N. Jayarathna, J. Lanel, Z. Juman, Five years of multi-depot vehicle routing problems, Journal of Sustainable Development of Transport and Logistics 5 (2) (2020) 109–123. https://doi.org/10.14254/jsdtl.2020.5-2.10.

[23]

J.W. Joubert, An initial solution heuristic for the vehicle routing and scheduling problem, University of Pretoria, 2007, [PhD Thesis].

[24]

S. Karakatič, V. Podgorelec, A survey of genetic algorithms for solving multi depot vehicle routing problem, Applied Soft Computing 27 (2015) 519–532,.

Digital Library

[25]

S. Kirkpatrick, C.D. Gelatt Jr, M.P. Vecchi, Optimization by simulated annealing. Science 220 (1983) 671–680.

[26]

G.D. Konstantakopoulos, S.P. Gayialis, E.P. Kechagias, Vehicle routing problem and related algorithms for logistics distribution: A literature review and classification, Operational Research 22 (3) (2022) 2033–2062,.

[27]

J. Li, T. Li, Y. Yu, Z. Zhang, P.M. Pardalos, Y. Zhang, Y. Ma, Discrete firefly algorithm with compound neighborhoods for asymmetric multi-depot vehicle routing problem in the maintenance of farm machinery, Applied Soft Computing 81 (2019),.

Digital Library

[28]

J. Li, R. Wang, T. Li, Z. Lu, P.M. Pardalos, Benefit analysis of shared depot resources for multi-depot vehicle routing problem with fuel consumption, Transportation Research Part D: Transport and Environment 59 (2018) 417–432.

[29]

Y. Li, H. Soleimani, M. Zohal, An improved ant colony optimization algorithm for the multi-depot green vehicle routing problem with multiple objectives, Journal of Cleaner Production 227 (2019) 1161–1172.

[30]

Y. Liu, An optimization-driven dynamic vehicle routing algorithm for on-demand meal delivery using drones, Computers & Operations Research 111 (2019) 1–20,.

Digital Library

[31]

I. Malheiros, R. Ramalho, B. Passeti, T. Bulhões, A. Subramanian, A hybrid algorithm for the multi-depot heterogeneous dial-a-ride problem, Computers & Operations Research 129 (2021),.

[32]

S.T.W. Mara, R. Norcahyo, P. Jodiawan, L. Lusiantoro, A.P. Rifai, A survey of adaptive large neighborhood search algorithms and applications, Computers & Operations Research 146 (2022).

[33]

R. Masson, F. Lehuédé, O. Péton, An adaptive large neighborhood search for the pickup and delivery problem with transfers, Transportation Science 47 (3) (2013) 344–355,.

Digital Library

[34]

J.R. Montoya-Torres, J.L. Franco, S.N. Isaza, H.F. Jiménez, N. Herazo-Padilla, A literature review on the vehicle routing problem with multiple depots, Computers & Industrial Engineering 79 (2015) 115–129,.

[35]

Y. Nagata, Efficient evolutionary algorithm for the vehicle routing problem with time windows: Edge assembly crossover for the VRPTW, IEEE Congress on Evolutionary Computation 2007 (2007) 1175–1182,.

[36]

M. Okulewicz, J. Mańdziuk, A metaheuristic approach to solve dynamic vehicle routing problem in continuous search space, Swarm and Evolutionary Computation 48 (2019) 44–61,.

[37]

G. Ozbaygin, M. Savelsbergh, An iterative re-optimization framework for the dynamic vehicle routing problem with roaming delivery locations, Transportation Research Part B: Methodological 128 (2019) 207–235,.

[38]

V. Pillac, M. Gendreau, C. Guéret, A.L. Medaglia, A review of dynamic vehicle routing problems, European Journal of Operational Research 225 (1) (2013) 1–11,.

[39]

D. Pisinger, S. Ropke, Large neighborhood search, Handbook of Metaheuristics 99–127 (2019),.

[40]

H.N. Psaraftis, M. Wen, C.A. Kontovas, Dynamic vehicle routing problems: Three decades and counting, Networks 67 (1) (2016) 3–31,.

Digital Library

[41]

B.H.O. Rios, E.C. Xavier, F.K. Miyazawa, P. Amorim, E. Curcio, M.J. Santos, Recent dynamic vehicle routing problems: A survey, Computers & Industrial Engineering 160 (2021).

[42]

S. Ropke, D. Pisinger, An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows, Transportation Science 40 (4) (2006) 455–472,.

Digital Library

[43]

M.E.H. Sadati, D. Aksen, N. Aras, A trilevel r-interdiction selective multi-depot vehicle routing problem with depot protection, Computers & Operations Research 123 (2020),.

[44]

M.E.H. Sadati, B. Çatay, A hybrid variable neighborhood search approach for the multi-depot green vehicle routing problem, Transportation Research Part E: Logistics and Transportation Review 149 (2021),.

[45]

M.E.H. Sadati, B. Çatay, D. Aksen, An efficient variable neighborhood search with tabu shaking for a class of multi-depot vehicle routing problems, Computers & Operations Research 133 (2021).

Digital Library

[46]

M.W. Savelsbergh, Local search in routing problems with time windows, Ann. Oper. Res. 4 (1985) 285–305,.

[47]

M. Schiffer, G. Walther, An adaptive large neighborhood search for the location-routing problem with intra-route facilities, Transportation Science 52 (2) (2018) 331–352,.

Digital Library

[48]

P. Shaw, A new local search algorithm providing high quality solutions to vehicle routing problems, Dept of Computer Science, University of Strathclyde, Glasgow, Scotland, UK, APES Group, 1997, p. 46.

[49]

P. Shaw, Using constraint programming and local search methods to solve vehicle routing problems, International Conference on Principles and Practice of Constraint Programming (1998) 417–431.

[50]

N. Soeffker, M.W. Ulmer, D.C. Mattfeld, Stochastic dynamic vehicle routing in the light of prescriptive analytics: A review, European Journal of Operational Research. (2021).

[51]

A. Soriano, M. Gansterer, R.F. Hartl, The multi-depot vehicle routing problem with profit fairness, International Journal of Production Economics 255 (2023),.

[52]

R. Turkeš, K. Sörensen, L.M. Hvattum, Meta-analysis of metaheuristics: Quantifying the effect of adaptiveness in adaptive large neighborhood search, European Journal of Operational Research 292 (2) (2021) 423–442,.

[53]

M.W. Ulmer, J.C. Goodson, D.C. Mattfeld, M. Hennig, Offline–online approximate dynamic programming for dynamic vehicle routing with stochastic requests, Transportation Science 53 (1) (2019) 185–202,.

Digital Library

[54]

T. Vidal, G. Laporte, P. Matl, A concise guide to existing and emerging vehicle routing problem variants, European Journal of Operational Research 286 (2) (2020) 401–416,.

[55]

B.S. Vieira, G.M. Ribeiro, L. Bahiense, Metaheuristics with variable diversity control and neighborhood search for the Heterogeneous Site-Dependent Multi-depot Multi-trip Periodic Vehicle Routing Problem, Computers & Operations Research 153 (2023),.

Digital Library

[56]

F.Y. Vincent, P. Jodiawan, A. Gunawan, An Adaptive Large Neighborhood Search for the green mixed fleet vehicle routing problem with realistic energy consumption and partial recharges, Applied Soft Computing 105 (2021).

[57]

C. Wang, C. Guo, X. Zuo, Solving multi-depot electric vehicle scheduling problem by column generation and genetic algorithm, Applied Soft Computing 112 (2021),.

[58]

F. Wang, F. Liao, Y. Li, X. Yan, X. Chen, An ensemble learning based multi-objective evolutionary algorithm for the dynamic vehicle routing problem with time windows, Computers & Industrial Engineering 154 (2021),.

[59]

Y. Wang, S. Peng, X. Zhou, M. Mahmoudi, L. Zhen, Green logistics location-routing problem with eco-packages, Transportation Research Part E: Logistics and Transportation Review 143 (2020).

[60]

Y. Wang, J. Zhe, X. Wang, J. Fan, Z. Wang, H. Wang, Collaborative multicenter reverse logistics network design with dynamic customer demands, Expert Systems with Applications 206 (2022).

[61]

M. Wen, W. Sun, Y. Yu, J. Tang, K. Ikou, An adaptive large neighborhood search for the larger-scale multi depot green vehicle routing problem with time windows, Journal of Cleaner Production 374 (2022),.

[62]

W. Wu, Y. Lin, R. Liu, W. Jin, The multi-depot electric vehicle scheduling problem with power grid characteristics, Transportation Research Part B: Methodological 155 (2022) 322–347,.

[63]

X. Xiang, Y. Tian, X. Zhang, J. Xiao, Y. Jin, A pairwise proximity learning-based ant colony algorithm for dynamic vehicle routing problems, IEEE Transactions on Intelligent Transportation Systems 23 (6) (2021) 5275–5286,.

[64]

G. Xue, Y. Wang, X. Guan, Z. Wang, A combined GA-TS algorithm for two-echelon dynamic vehicle routing with proactive satellite stations, Computers & Industrial Engineering 164 (2022).

[65]

Z. Yang, J.-P. van Osta, B. van Veen, R. van Krevelen, R. van Klaveren, A. Stam, J. Kok, T. Bäck, M. Emmerich, Dynamic vehicle routing with time windows in theory and practice, Natural Computing 16 (1) (2017) 119–134,.

Digital Library

[66]

B. Yu, N. Ma, W. Cai, T. Li, X. Yuan, B. Yao, Improved ant colony optimisation for the dynamic multi-depot vehicle routing problem, International Journal of Logistics Research and Applications 16 (2) (2013) 144–157,.

[67]

J. Zhang, K. Luo, A.M. Florio, T. Van Woensel, Solving large-scale dynamic vehicle routing problems with stochastic requests, European Journal of Operational Research 306 (2) (2023) 596–614,.

[68]

Q. Zhang, Z. Wang, M. Huang, Y. Yu, S.-C. Fang, Heterogeneous multi-depot collaborative vehicle routing problem, Transportation Research Part B: Methodological 160 (2022) 1–20,.

[69]

L. Zhen, C. Ma, K. Wang, L. Xiao, W. Zhang, Multi-depot multi-trip vehicle routing problem with time windows and release dates, Transportation Research Part E: Logistics and Transportation Review 135 (2020).

[70]

L. Zhou, R. Baldacci, D. Vigo, X. Wang, A multi-depot two-echelon vehicle routing problem with delivery options arising in the last mile distribution, European Journal of Operational Research 265 (2) (2018) 765–778,.

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Published In

cover image Computers and Industrial Engineering

Computers and Industrial Engineering Volume 191, Issue C

May 2024

999 pages

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Elsevier Ltd.

Publisher

Pergamon Press, Inc.

United States

Publication History

Published: 18 July 2024

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