A Simultaneous Location, Routing and Scheduling Model for Transporting Evacuees with Time Window and Multiple Depots

Document Type : Research Paper

Authors

1 Faculty of Engineering, Iran University of Science and Technology, Tehran, Iran

2 Faculty of Engineering, University of Tehran, Iran

Abstract

After natural disasters and unexpected events, one of the most vital actions of disaster response phase is to transport evacuees from disaster areas to safe places. In this paper, decisions of the location of shelters and routing and scheduling of relief vehicles at the same time are modeled for a two-level network including depots of vehicles, affected areas, and shelters. In the evacuation operation, the possibility of servicing to evacuees in each affected area by several vehicles, existence of multiple depots of heterogeneous vehicles and time window constraints are considered. To solve the proposed model and demonstrate its efficiency, a numerical example was solved by exact method, and it was done the sensitivity analysis on the problem main parameters. Results show that the number of shelters to locate evacuees and capacity of relief vehicles effects on total times for vehicles to get to affected areas and shelters.

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Main Subjects

References

1-       Ngueveu, S.U., Prins, C. and Calvo, R. W. (2010). “An effective memetic algorithm for the cumulative capacitated vehicle routing problem”, Computers & Operations Research., Vol. 37, No. 11, PP. 1877–1885.
2-       Ribeiro, G. M. and Laporte, G. (2012). “An adaptive large neighborhood search heuristic for the cumulative capacitated vehicle routing problem.” Computers and Operations Research., Vol. 39, No. 3, PP. 728–735.
3-       Ke, L. and Feng, Z. (2013). “A two-phase metaheuristic for the cumulative capacitated vehicle routing problem”, Computers and Operations Research., Vol. 40, No. 2, PP. 633–638.
4-       Ozsoydan, F. B. and Sipahioglu, A. (2013). “Heuristic solution approaches for the cumulative capacitated vehicle routing problem”, Optimization., Vol. 62, No. 10, PP. 1321–1340.
5-       Özdamar, L., Aksu, D.T. and Ergüneş, B. (2014). “Coordinating debris cleanup operations in post disaster road networks”, Socio-Economic Planning Sciences., Vol. 48, No. 4, PP. 249–262.
6-       Wohlgemuth, S., Oloruntoba, R. and Clausen, U. (2012). “Dynamic vehicle routing with anticipation in disaster relief”, Socio-Economic Planning Sciences., Vol. 46, No. 4, PP. 261–271.
7-       Lee, K., Lei, L., Pinedo, M. and Wang, S. (2013a). “Operations scheduling with multiple resources and transportation considerations”, International Journal of Production Research., Vol. 51, No. 23-24, PP. 7071-7090.
8-       Lee, K., Lei, L. and Dong, H. (2013b). “A Solvable Case of Emergency Supply Chain Scheduling Problem with Multi-stage Lead Times”, Journal of Supply Chain and Operations Management., Vol. 11, No. 2, PP. 30–45.
9-       Gan, X., Wang, Y., Kuang, J., Yu, Y. and Niu, B. (2014). “Emergency Vehicle Scheduling Problem with Time Utility in Disasters”, Mathematical Problems in Engineering, Vol. 2015, PP. 1-7.
10-   Pramudita, A., Taniguchi, E. and Qureshi, A.G. (2014). “Location and Routing Problems of Debris Collection Operation after Disasters with Realistic Case Study”, Procedia-Social and Behavioral Sciences., Vol. 125, PP. 445–458.
11-   Wex, F., Schryen, G., Feuerriegel, S. and Neumann, D. (2014). “Emergency response in natural disaster management: Allocation and scheduling of rescue units.” European Journal of Operational Research., Vol. 235, No. 3, PP. 697–708.
12-   Bish, D. R. (2011). “Planning for a bus-based evacuation”, OR Spectrum., Vol. 33, No. 3, PP. 629–654.
13-   Abdelgawad, H. and Abdulhai, B. (2011). “Large-scale evacuation using subway and bus transit: approach and application in city of Toronto”, Journal of Transportation Engineering, Vol. 138, No. 10, PP. 1215–1232.
14-   Hamedi, M., Haghani, A. and Yang, S. (2012). “Reliable transportation of humanitarian supplies in disaster response: model and heuristic”, Procedia-Social and Behavioral Sciences., Vol. 54, PP. 1205–1219.
15-   Rath, S. and Gutjahr, W. J. (2014). “A math-heuristic for the warehouse location–routing problem in disaster relief”, Computers and Operations Research., Vol. 42, PP. 25–39.
16-   Gan, X., Wang, Y., Yu, Y. and Niu, B. (2013). “An emergency vehicle scheduling problem with time utility based on particle swarm optimization”, In Proceedings of the 9th international conference on Intelligent Computing Theories and Technology, PP. 614–623.
17-   Wex, F., Schryen, G. and Neumann, D. (2012). “Operational emergency response under informational uncertainty: a fuzzy optimization model for scheduling and allocating rescue units”, In Proceedings of the 9th International ISCRAM Conference, PP. 1-10.
18-   Talarico, L., Meisel, F. and Sorensen, K. (2015) “Ambulance routing for disaster response with patient groups”, Computers and Operations Research, Vol. 56, PP. 120–133.
19-   Caunhye, A. M., Zhang, Y., Li, M. and Nie, X. (2016). “A location-routing model for prepositioning and distributing emergency supplies”, Transportation Research Part E: Logistics and Transportation Review, Vol. 90, PP. 161–176.
 
Advances in Industrial Engineering
Volume 51, Issue 2
July 2017
Pages 195-206

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