Top

Neural Computing and Applications

Published in:

15-10-2022 | Original Article

Multiobjective problem modeling of the capacitated vehicle routing problem with urgency in a pandemic period

Published in: Neural Computing and Applications | Issue 5/2023

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

This research is based on the capacitated vehicle routing problem with urgency where each vertex corresponds to a medical facility with a urgency level and the traveling vehicle could be contaminated. This contamination is defined as the infectiousness rate, which is defined for each vertex and each vehicle. At each visited vertex, this rate for the vehicle will be increased. Therefore time-total distance it is desired to react to vertex as fast as possible- and infectiousness rate are main issues in the problem. This problem is solved with multiobjective optimization algorithms in this research. As a multiobjective problem, two objectives are defined for this model: the time and the infectiousness, and will be solved using multiobjective optimization algorithms which are nondominated sorting genetic algorithm (NSGAII), grid-based evolutionary algorithm GrEA, hypervolume estimation algorithm HypE, strength Pareto evolutionary algorithm shift-based density estimation SPEA2-SDE, and reference points-based evolutionary algorithm.

previous article Few-shot learning for modeling cyber physical systems in non-stationary environments

next article Joint semantic embedding with structural knowledge and entity description for knowledge representation learning

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Available only for authorised users

Anderluh A, Nolz PC, Hemmelmayr VC, Crainic TG (2021) Multi-objective optimization of a two-echelon vehicle routing problem with vehicle synchronization and ‘grey zone’ customers arising in urban logistics. Eur J Oper Res 289(3):940–958. https://doi.org/10.1016/j.ejor.2019.07.049CrossRefMATH

Araghi MET, Tavakkoli-Moghaddam R, Jolai F, Molana SMH (2021) A green multi-facilities open location-routing problem with planar facility locations and uncertain customer. J Clean Prod 282:124343. https://doi.org/10.1016/j.jclepro.2020.124343CrossRef

Bader J, Zitzler E (2011) Hype an algorithm for fast hypervolume-based many-objective optimization. Evol Comput 19(1):45–76. https://doi.org/10.1162/evco-a-00009CrossRef

Behnke M, Kirschstein T, Bierwirth C (2021) A column generation approach for an emission-oriented vehicle routing problem on a multigraph. Eur J Oper Res 288(3):794–809. https://doi.org/10.1016/j.ejor.2020.06.035CrossRefMATH

Beliaev M, Biyik E, Lazar DA, Wang WZ, Sadigh D, Pedarsani R (2021) Incentivizing routing choices for safe and efficient transportation in the face of the covid-19 pandemic. In: Proceedings of the ACM/IEEE 12th International Conference on Cyber-Physical Systems, pp. 1–11. ACM. https://doi.org/10.1145/3450267.3450546

Brandstatter C (2019) A metaheuristic algorithm and structured analysis for the line-haul feeder vehicle routing problem with time windows. CEJOR 29(1):247–289. https://doi.org/10.1007/s10100-019-00625-0CrossRefMATH

Cai L, Lv W, Xiao L, Xu Z (2021) Total carbon emissions minimization in connected and automated vehicle routing problem with speed variables. Expert Syst Appl 165:113910. https://doi.org/10.1016/j.eswa.2020.113910CrossRef

Cao B, Zhang W, Wang X, Zhao J, Gu Y, Zhang Y (2021) A memetic algorithm based on twoarch2 for multi-depot heterogeneous-vehicle capacitated arc routing problem. Swarm Evol Comput 63:100864. https://doi.org/10.1016/j.swevo.2021.100864CrossRef

Cao JX, Wang X, Gao J (2021) A two-echelon location-routing problem for biomass logistics systems. Biosys Eng 202:106–118. https://doi.org/10.1016/j.biosystemseng.2020.12.007CrossRef

10.

Cao JX, Zhang Z, Zhou Y (2021) A location-routing problem for biomass supply chains. Comput Ind Eng 152:107017. https://doi.org/10.1016/j.cie.2020.107017CrossRef

11.

Cristofides N (1979) etc: Combinatorial optimization. Wiley, New Jersey

12.

Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: Nsga-ii. IEEE Trans Evol Comput 6(2):182–197. https://doi.org/10.1109/4235.996017CrossRef

13.

Deb K, Thiele L, Laumanns M, Zitzler E (2005) Scalable test problems for evolutionary multiobjective optimization. Advanced information and knowledge processing. Springer-Verlag, Berlin, pp 105–145. https://doi.org/10.1007/1-84628-137-7-6CrossRef

14.

Dewi SK, Utama DM (2020) A new hybrid whale optimization algorithm for green vehicle routing problem. Syst Sci Control Eng 9(1):61–72. https://doi.org/10.1080/21642583.2020.1863276CrossRef

15.

Euchi J, Sadok A (2021) Hybrid genetic-sweep algorithm to solve the vehicle routing problem with drones. Phys Commun 44:101236. https://doi.org/10.1016/j.phycom.2020.101236CrossRef

16.

Theurich F, Fischer A, Scheithauer G (2021) A branch-and-bound approach for a vehicle routing problem with customer costs. EURO J Comput Optim 9:1–11. https://doi.org/10.1016/j.ejco.2020.100003CrossRef

17.

Fan H, Zhang Y, Tian P, Lv Y, Fan H (2021) Time-dependent multi-depot green vehicle routing problem with time windows considering temporal-spatial distance. Comput Oper Res 129:105211. https://doi.org/10.1016/j.cor.2021.105211CrossRefMATH

18.

Gamchi NS, Torabi SA, Jolai F (2020) A novel vehicle routing problem for vaccine distribution using sir epidemic model. OR Spectrum 43(1):155–188. https://doi.org/10.1007/s00291-020-00609-6CrossRef

19.

Haixiang G, Fang W, Wenwen P, Mingyun G (2021) Period sewage recycling vehicle routing problem based on real-time data. J Clean Prod 288:125628. https://doi.org/10.1016/j.jclepro.2020.125628CrossRef

20.

Jalilvand M, Bashiri M, Nikzad E (2021) An effective progressive hedging algorithm for the two-layers time window assignment vehicle routing problem in a stochastic environment. Expert Syst Appl 165:113877. https://doi.org/10.1016/j.eswa.2020.113877CrossRef

21.

Jiang F, Dong L, Dai Q (2022) Designing a mixed multilayer wavelet neural network for solving eri inversion problem with massive amounts of data: A hybrid stgwo-gd learning approach. IEEE Trans Cybern 52(2):925–936. https://doi.org/10.1109/tcyb.2020.2990319CrossRef

22.

Jiang F, Dong L, Wang K, Yang K, Pan C (2022) Distributed resource scheduling for large-scale mec systems: a multiagent ensemble deep reinforcement learning with imitation acceleration. IEEE Internet Things J 9(9):6597–6610. https://doi.org/10.1109/jiot.2021.3113872CrossRef

23.

Jiang F, Wang K, Dong L, Pan C, Xu W, Yang K (2020) Deep-learning-based joint resource scheduling algorithms for hybrid mec networks. IEEE Internet Things J 7(7):6252–6265. https://doi.org/10.1109/jiot.2019.2954503CrossRef

24.

Ju B, Kim M, Moon I (2021) Vehicle routing problem considering reconnaissance and transportation. Sustainability 13(6):3188. https://doi.org/10.3390/su13063188CrossRef

25.

Khoo TS, Mohammad BB (2021) The parallelization of a two-phase distributed hybrid ruin-and-recreate genetic algorithm for solving multi-objective vehicle routing problem with time windows. Expert Syst Appl 168:114408. https://doi.org/10.1016/j.eswa.2020.114408CrossRef

26.

Lalla-Ruiz E, Mes M (2020) Mathematical formulations and improvements for the multi-depot open vehicle routing problem. Optim Lett 15(1):271–286. https://doi.org/10.1007/s11590-020-01594-zCrossRefMATH

27.

Li J, Xin L, Cao Z, Lim A, Song W, Zhang J (2021) Heterogeneous attentions for solving pickup and delivery problem via deep reinforcement learning. IEEE Trans Intell Transp Syst. https://doi.org/10.1109/tits.2021.3056120CrossRef

28.

Li M, Yang S, Liu X (2014) Shift-based density estimation for pareto-based algorithms in many-objective optimization. IEEE Trans Evol Comput 18(3):348–365. https://doi.org/10.1109/tevc.2013.2262178CrossRef

29.

Liu Y, Gong D, Sun X, Zhang Y (2017) Many-objective evolutionary optimization based on reference points. Appl Soft Comput 50:344–355. https://doi.org/10.1016/j.asoc.2016.11.009CrossRef

30.

Malheiros I, Ramalho R, Passeti B, Bulhoes T, Subramanian A (2021) A hybrid algorithm for the multi-depot heterogeneous dial-a-ride problem. Comput Oper Res 129:105196. https://doi.org/10.1016/j.cor.2020.105196CrossRefMATH

31.

Martin-Santamaria R, Lopez-Sanchez AD, Delgado-Jalon ML, Colmenar JM (2021) An efficient algorithm for crowd logistics optimization. Mathematics 9(5):509. https://doi.org/10.3390/math905050CrossRef

32.

Mojtahedi M, Fathollahi-Fard AM, Tavakkoli-Moghaddam R, Newton S (2021) Sustainable vehicle routing problem for coordinated solid waste management. J Ind Inf Integr 23:100220. https://doi.org/10.1016/j.jii.2021.100220CrossRef

33.

Niu Y, Zhang Y, Cao Z, Gao K, Xiao J, Song W, Zhang F (2021) Mimoa: a membrane-inspired multi-objective algorithm for green vehicle routing problem with stochastic demands. Swarm Evol Comput 60:100767. https://doi.org/10.1016/j.swevo.2020.100767CrossRef

34.

Nucamendi-Guillen S, Padilla AG, Olivares-Benitez E, Moreno-Vega JM (2021) The multi-depot open location routing problem with a heterogeneous fixed fleet. Expert Syst Appl 165:113846. https://doi.org/10.1016/j.eswa.2020.113846CrossRef

35.

Osorio-Mora A, Soto-Bustos M, Gatica G, Palominos P, Linfati R (2021) The multi-depot cumulative vehicle routing problem with mandatory visit times and minimum delayed latency. IEEE Access 9:27210–27225. https://doi.org/10.1109/access.2021.3058242CrossRef

36.

Pan B, Zhang Z, Lim A (2021) A hybrid algorithm for time-dependent vehicle routing problem with time windows. Comput Oper Res 128:105193. https://doi.org/10.1016/j.cor.2020.105193CrossRefMATH

37.

Park H, Son D, Koo B, Jeong B (2021) Waiting strategy for the vehicle routing problem with simultaneous pickup and delivery using genetic algorithm. Expert Syst Appl 165:113959. https://doi.org/10.1016/j.eswa.2020.113959CrossRef

38.

Quirion-Blais O, Chen L (2021) A case-based reasoning approach to solve the vehicle routing problem with time windows and drivers’ experience. Omega 102:102340. https://doi.org/10.1016/j.omega.2020.102340CrossRef

39.

Saint-Guillain M, Paquay C, Limbourg S (2021) Time-dependent stochastic vehicle routing problem with random requests: Application to online police patrol management in brussels. Eur J Oper Res 292(3):869–885. https://doi.org/10.1016/j.ejor.2020.11.007CrossRefMATH

40.

Schott JR (1995) Fault tolerant design using single and multicriteria genetic algorithm optimizations. M.S. thesis

41.

Sherif SU, Asokan P, Sasikumar P, Mathiyazhagan K, Jerald J (2021) Integrated optimization of transportation, inventory and vehicle routing with simultaneous pickup and delivery in two-echelon green supply chain network. J Clean Prod 287:125434. https://doi.org/10.1016/j.jclepro.2020.125434CrossRef

42.

Sitek P, Wikarek J, Rutczynska-Wdowiak K, Bocewicz G, Banaszak Z (2021) Optimization of capacitated vehicle routing problem with alternative delivery, pick-up and time windows: A modified hybrid approach. Neurocomputing 423:670–678. https://doi.org/10.1016/j.neucom.2020.02.126CrossRef

43.

Tao N, Shishasha S, Peng Z, Tao G (2020) Disruption management decision model for vrpsdp under changes of customer distribution demand. J Ambient Intell Humaniz Comput 12(2):2053–2063. https://doi.org/10.1007/s12652-020-02304-4CrossRef

44.

Theeb NA, Hayajneh M, Qubelat NA (2020) Optimization of logistic plans with adopting the green technology considerations by utilizing electric vehicle routing problem. Ind Eng Manag Syst 19(4):774–789. https://doi.org/10.7232/iems.2020.19.4.774CrossRef

45.

Tikani H, Setak M, Demir E (2021) A risk-constrained time-dependent cash-in-transit routing problem in multigraph under uncertainty. Eur J Oper Res 293(2):703–730. https://doi.org/10.1016/j.ejor.2020.12.020CrossRefMATH

46.

Tookanlou MB, Kani SAP, Marzband M (2021) A comprehensive day-ahead scheduling strategy for electric vehicles operation. Int J Electr Power Energy Syst 131:106912. https://doi.org/10.1016/j.ijepes.2021.106912CrossRef

47.

Vieira YEM, de Mello Bandeira RA, da Silva Junior OS (2021) Multi-depot vehicle routing problem for large scale disaster relief in drought scenarios: the case of the brazilian northeast region. Int J Disaster Risk Reduct 58:102193. https://doi.org/10.1016/j.ijdrr.2021.102193CrossRef

48.

Wang N, Sun Y, Wang H (2021) An adaptive memetic algorithm for dynamic electric vehicle routing problem with time-varying demands. Math Probl Eng 2021:1–10. https://doi.org/10.1155/2021/6635749CrossRef

49.

Wang X, Lin N, Li Y, Shi Y, Ruan J (2021) An integrated modeling method for collaborative vehicle routing: facilitating the unmanned micro warehouse pattern in new retail. Expert Syst Appl 168:114307. https://doi.org/10.1016/j.eswa.2020.114307CrossRef

50.

Wang Y, Li Q, Guan X, Xu M, Liu Y, Wang H (2021) Two-echelon collaborative multi-depot multi-period vehicle routing problem. Expert Syst Appl 167:114201. https://doi.org/10.1016/j.eswa.2020.114201CrossRef

51.

Wang Y, Zhang J, Guan X, Xu M, Wang Z, Wang H (2021) Collaborative multiple centers fresh logistics distribution network optimization with resource sharing and temperature control constraints. Expert Syst Appl 165:113838. https://doi.org/10.1016/j.eswa.2020.113838CrossRef

52.

Wang YN, Wu LH, Yuan XF (2009) Multi-objective self-adaptive differential evolution with elitist archive and crowding entropy-based diversity measure. Soft Comput 14(3):193–209. https://doi.org/10.1007/s00500-008-0394-9CrossRef

53.

While L, Hingston P, Barone L, Huband S (2006) A faster algorithm for calculating hypervolume. IEEE Trans Evol Comput 10(1):29–38. https://doi.org/10.1109/tevc.2005.851275CrossRef

54.

Wu Y, Song W, Cao Z, Zhang J, Lim A (2021) Learning improvement heuristics for solving routing problems. IEEE Trans Neural Netw Learn Syst. https://doi.org/10.1109/tnnls.2021.3068828CrossRef

55.

Yang S, Li M, Liu X, Zheng J (2013) A grid-based evolutionary algorithm for many-objective optimization. IEEE Trans Evol Comput 17(5):721–736. https://doi.org/10.1109/tevc.2012.2227145CrossRef

56.

Yang S, Ning L, Tong LC, Shang P (2021) Optimizing electric vehicle routing problems with mixed backhauls and recharging strategies in multi-dimensional representation network. Expert Syst Appl 176:114804. https://doi.org/10.1016/j.eswa.2021.114804CrossRef

57.

Yin F, Zhao Y (2021) Optimizing vehicle routing via stackelberg game framework and distributionally robust equilibrium optimization method. Inf Sci 557:84–107. https://doi.org/10.1016/j.ins.2020.12.057CrossRefMATH

58.

Yu VF, Jodiawan P, Gunawan A (2021) An adaptive large neighborhood search for the green mixed fleet vehicle routing problem with realistic energy consumption and partial recharges. Appl Soft Comput 105:107251. https://doi.org/10.1016/j.asoc.2021.107251CrossRef

59.

hua Zeng M, Wang M, Chen Y, Yang Z (2021) Dynamic evacuation optimization model based on conflict-eliminating cell transmission and split delivery vehicle routing. Saf Sci 137:105166. https://doi.org/10.1016/j.asoc.2021.107251CrossRef

60.

Zhang W, Chen Z, Zhang S, Cai Y (2020) Dynamic multi-stage failure-specific cooperative recourse strategy for logistics with simultaneous pickup and delivery. Soft Comput 25(5):3795–3812. https://doi.org/10.1007/s00500-020-05408-3CrossRefMATH

61.

Zhu Y, Lee KY, Wang Y (2021) Adaptive elitist genetic algorithm with improved neighbor routing initialization for electric vehicle routing problems. IEEE Access 9:16661–16671. https://doi.org/10.1109/access.2021.3053285CrossRef

Title: Multiobjective problem modeling of the capacitated vehicle routing problem with urgency in a pandemic period
Publication date: 15-10-2022
Published in: Neural Computing and Applications / Issue 5/2023
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-022-07921-y

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Springer Professional "Wirtschaft+Technik"

Other articles of this Issue 5/2023

Influence maximization based on maximum inner product search

Disturbance-observer-based adaptive dynamic surface control for nonlinear systems with input dead-zone and delay using neural networks

Boosting Archimedes optimization algorithm using trigonometric operators based on feature selection for facial analysis

Unsupervised active learning with loss prediction

PAENL: personalized attraction enhanced network learning for recommendation

High spatial resolution remote sensing image segmentation based on the multiclassification model and the binary classification model

Premium Partner