Browse > Article
http://dx.doi.org/10.9708/jksci.2019.24.01.167

Multi Objective Vehicle and Drone Routing Problem with Time Window  

Park, Tae Joon (Dept. of Yonsei School of Business, Yonsei University)
Chung, Yerim (Dept. of Yonsei School of Business, Yonsei University)
Publication Information
Journal of the Korea Society of Computer and Information / v.24, no.1, 2019 , pp. 167-178 More about this Journal
Abstract
In this paper, we study the multi-objectives vehicle and drone routing problem with time windows, MOVDRPTW for short, which is defined in an urban delivery network. We consider the dual modal delivery system consisting of drones and vehicles. Drones are used as a complement to the vehicle and operate in a point to point manner between the depot and the customer. Customers make various requests. They prefer to receive delivery services within the predetermined time range and some customers require fast delivery. The purpose of this paper is to investigate the effectiveness of the delivery strategy of using drones and vehicles together with a multi-objective measures. As experiment datasets, we use the instances generated based on actual courier delivery data. We propose a hybrid multi-objective evolutionary algorithm for solving MOVDRPTW. Our results confirm that the vehicle-drone mixed strategy has 30% cost advantage over vehicle only strategy.
Keywords
Drone; Multi-Objective Vehicle Routing Problem; Hybrid-Meta-Heuristics; Evolutionary Algorithm; Distribution Network;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Q. M. Ha, Q. Y. Deville, Q. D. Pham, and M. H. Ha, "Heuristic methods for the Traveling Salesman Problem with Drone", arXiv preprint arXiv:1509.08764, 2015.
2 Q. M. Ha, Q. Y. Deville, Q. D. Pham, and M.H. Ha, "On the Min-cost Traveling Salesman Problem with Drone". arXiv preprint arXiv:1509.08764, 2015.
3 Y. Chung, T. Park, and Y. Min, "Usefulness of Drones in the Urban Delivery System: Solving the Vehicle and Drone Routing Problem with Time Window", Journal of the Korean Operations Research and Management Science Society, Vol.41 No.3 ,pp. 75-96, 2016.   DOI
4 T. Back, "Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithm.", Oxford university press, 1996.
5 G. Laporte, M. Gendreau, J. Y. Potvin, and F. Semet, "Classical and modern heuristics for the vehicle routing problem", International transactions in operational research, Vol. 7, No. 4-5, pp. 285-300, 2000.   DOI
6 B. Ombuki, B. J. Ross, and F. Hanshar, "Multi-objective genetic algorithms for vehicle routing problem with time windows", Applied Intelligence, Vol. 24, No. 1, pp. 17-30, 2006.   DOI
7 O. Braysy, W. Dullaert, and M. Gendreau, "Evolutionary algorithms for the vehicle routing problem with time windows", Journal of Heuristics, Vol. 10, No. 6, pp.587-611, 2004.   DOI
8 S. C. Hong, and Y. B. Park, "A heuristic for bi-objective vehicle routing with time window constraints", International Journal of Production Economics, Vol. 62, No. 3, pp. 249-258, 1999.   DOI
9 K. Deb, "Multi-Objective Optimization Using Evolutionary Algorithms", John Wiley& Sons. Inc., New York, NY, 2001.
10 E. Zitzler, M. Laumanns, and L. Thiele, SPEA2, "Improving the strength Pareto evolutionary algorithm", 2001.
11 E. G. Talbi, "Metaheuristics: from design to implementation", Vol. 74, John Wiley & Sons, 2009.
12 J. Berger, and M. Barkaoui, "A hybrid genetic algorithm for the capacitated vehicle routing problem", In Genetic and evolutionary computation conference, pp. 646-656. Springer Berlin Heidelberg, July 2003.
13 K. C. Tan, T. H. Lee, Y. H. Chew, and L. H. Lee, "A multiobjective evolutionary algorithm for solving vehicle routing problem with time windows", In Systems, Man and Cybernetics, 2003. IEEE International Conference, Vol. 1, pp. 361-366. IEEE, October, 2003.
14 O. Braysy, "Fast local searches for the vehicle routing problem with time windows", INFOR: Information Systems and Operational Research, Vol. 40, No. 4, pp. 319-330, 2002.   DOI
15 E. Zitzler, and L. Thiele, "An evolutionary algorithm for multiobjective optimization: The strength pareto approach", 1998.
16 W. Chaovalitwongse, D. Kim, and P. M. Pardalos, "GRASP with a new local search scheme for vehicle routing problems with time windows", Journal of Combinatorial Optimization, Vol. 7, No. 2, pp. 179-207, 2003.   DOI
17 F. Glover, "New ejection chain and alternating path methods for traveling salesman problems", Computer science and operations research, Vol. 449, pp. 491-507, 1992.
18 C. A. C. Coello, G. B. Lamont, and D. A. Van Veldhuizen, "Evolutionary algorithms for solving multi-objective problems", (Vol. 5, New York: Springer, 2007.
19 C. C. Murray and A. G. Chu, "The flying sidekick traveling salesman problem: Optimization of drone-assisted parcel delivery", Transportation Research Part C: Emerging Technologies, Vol. 54, pp. 86-109, 2015.   DOI
20 N. Agatz, P. Bouman, and M. Schmidt, "Optimization approaches for the traveling salesman problem with drone", 2016.