Skip to main content

Advertisement

Log in

Disturbance management for vehicle routing with time window changes

  • Original Paper
  • Published:
Operational Research Aims and scope Submit manuscript

Abstract

In this paper, the issue of vehicle routing with time window changes is addressed. Considering the uncertainty of customers’ time windows in distribution activities, this paper used the theory of disturbance management. The objective is to minimize the negative impacts of the perturbation attributed to time window changes. The identification of time window change that would cause a perturbation to the current distribution plan was analyzed. In order to measure the negative impact, three metrics of disturbance were analyzed in this paper, including path deviation, service time deviation and cost deviation. Based on vehicles’ positions at the disturbance time, a disturbance recovery model regarding to time window changes of customers is established. A dispatching method that is based on tabu search was proposed to obtain a timely and optimal solution. Finally, the computational experiments indicate that the proposed method is feasible for solving this real-word problem and is more effective than other incident-handling methods.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Clausen J, Jesper H, Jesper L (2001) Disruption management. OR/MS 28(5):40–43

    Google Scholar 

  • Cordeau JF, Maischberger M (2012) A parallel iterated tabu search heuristic for vehicle routing problems. Comput Oper Res 39:2033–2050

    Article  Google Scholar 

  • Dantzig G, Ramser J (1959) The truck dispatching problem. Manag Sci 6(1):80–91

    Article  Google Scholar 

  • De Armas J, Batista BM (2015) Variable neighborhood search for a dynamic rich vehicle routing problem with time windows. Comput Ind Eng 85:120–131

    Article  Google Scholar 

  • Dhahri A, Zidi K, Ghedira K (2015) A variable neighborhood search for the vehicle routing problem with time windows and preventive maintenance activities. Electron Notes Discrete Math 47:229–236

    Article  Google Scholar 

  • Ding QL, Hu XP, Sun LJ, Wang YZ (2012) An improved ant colony optimization and its application to vehicle routing problem with time windows. Neurocomputing 98:101–107

    Article  Google Scholar 

  • Euchi J, Yassine A, Chabchoub H (2015) The dynamic vehicle routing problem: solution with hybrid metaheuristic approach. Swarm Evolut Comput 21:41–53

    Article  Google Scholar 

  • Ferrucci F, Bock S, Gendreau M (2013) A pro-active real-time control approach for dynamic vehicle routing problems dealing with the delivery of urgent goods. Eur J Oper Res 225(1):130–141

    Article  Google Scholar 

  • Goksal FP, Karaoglan I, Altiparmak F (2013) A hybrid discrete particle swarm optimization for vehicle routing problem with simultaneous pickup and delivery. Comput Ind Eng 65:39–53

    Article  Google Scholar 

  • Hà MH, Bostel N, Langevin A, Rousseau LM (2014) An exact algorithm and a metaheuristic for the generalized vehicle routing problem with flexible fleet size. Comput Oper Res 43:9–19

    Article  Google Scholar 

  • Häme L (2011) An adaptive insertion algorithm for the single-vehicle dial-a-ride problem with narrow time windows. Eur J Oper Res 209(1):11–22

    Article  Google Scholar 

  • He XF, Ma L (2013) Quantum-inspired ant colony algorithm for vehicle routing problem with time windows. Syst Eng Theory Practice 33(5):1255–1261

    Google Scholar 

  • Holland JH (1975) Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. University of Michigan Press, Ann Arbor

    Google Scholar 

  • Hu XP, Sun LJ, Wang YN (2011) A model for disruption management in urban distribution systems. J Manag Sci China 14(1):50–60

    Google Scholar 

  • Hu XP, Sun LJ, Liu LL (2013) A PAM approach to handling disruptions in real-time vehicle routing problems. Decis Support Syst 54:1380–1393

    Article  Google Scholar 

  • Karakatic S, Podgorelec V (2015) A survey of genetic algorithms for solving multi depot vehicle routing problem. Appl Soft Comput 27:519–532

    Article  Google Scholar 

  • Lenstra J, Rinnooy KA (1981) Complexity of vehicle routing and scheduling problems. Networks 11:221–227

    Article  Google Scholar 

  • Li JQ, Borenstein D, Mirchandani PB (2007) A decision support system for the single-depot vehicle rescheduling problem. Comput Oper Res 34(4):1008–1032

    Article  Google Scholar 

  • Liu X, Qi H (2008) Local search algorithm of dynamic vehicle routing problem with time window. J Traffic Trans Eng 8(5):114–120

    Google Scholar 

  • Liu M, Luo Z, Lim A (2015) A branch-and-cut algorithm for a realistic dial-a-ride problem. Trans Res Part B Methodol 81:267–288

    Article  Google Scholar 

  • Marinakis Y, Iordanidou GR, Marinaki M (2013) Particle swarm optimization for the vehicle routing problem with stochastic demands. Appl Soft Comput 13:1693–1704

    Article  Google Scholar 

  • Pillac V, Gendreau M, Guéret C, Medaglia AL (2013) A review of dynamic vehicle routing problems. Eur J Oper Res 225:1–11

    Article  Google Scholar 

  • Potvin JY, Xu Y, Benyahia I (2006) Vehicle routing and scheduling with dynamic travel times. Comput Oper Res 33:1129–1137

    Article  Google Scholar 

  • Razali NM (2015) An efficient genetic algorithm for large scale vehicle routing problem subject to precedence constraints. Soc Behav Sci 195:1922–1931

    Article  Google Scholar 

  • Reed M, Yiannakou A, Evering R (2014) An ant colony algorithm for the multi-compartment vehicle routing problem. Appl Soft Comput 15:169–176

    Article  Google Scholar 

  • Schyns M (2015) An ant colony system for responsive dynamic vehicle routing. Eur J Oper Res 245:704–718

    Article  Google Scholar 

  • Solomon M (2009) Solomon benchmark problems, http://www.idsia.ch/~luca/macs-vrptw/problems/welcome.html

  • Wang XP, Wu X, Hu XP (2010) A study of urgency vehicle routing disruption management problem. J Netw 5(12):452–455

    Google Scholar 

  • Yu G, Qi X (2004) Disruption Management: framework, models and applications. World Scientific Publishing Co. Pte. Ltd, Singapore

    Book  Google Scholar 

  • Yu G, Yang J (1999) Optimization applications in the airline industry. Springer, Berlin

    Google Scholar 

Download references

Acknowledgements

This research is supported by the National Natural Science Foundation of China (Grant No. 71372088).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hualong Yang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yang, H., Zhao, L., Ye, D. et al. Disturbance management for vehicle routing with time window changes. Oper Res Int J 20, 1093–1112 (2020). https://doi.org/10.1007/s12351-017-0363-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12351-017-0363-0

Keywords

Mathematics Subject Classification

Navigation