Authors: Ming Liu, Lindu Zhao, Hans-Jurgen Sebastian
Addresses: Institute of Systems Engineering, Southeast University, Nanjing 211189, China. ' Institute of Systems Engineering, Southeast University, Nanjing 210096, China. ' Deutsche Post Chair of Optimisation of Distribution Networks, RWTH Aachen University, 52062 Aachen, Germany
Abstract: In this paper, a unique forecasting model for the demand of emergency resources based on epidemic diffusion rule is constructed. We find that both the pure point-to-point delivery mode (PTP) and the pure multi-depot, multiple travelling salesmen delivery system (MMTS) are difficult to operate in an actual emergency situation. Thus, we propose a mixed-collaborative distribution mode, which can equilibrate the contradiction between these two pure modes. A special time window for such a mixed-collaborative mode is designed. A Genetic Algorithm (GA) is adopted to solve the optimisation model. At last, we compare it with these two pure distribution modes from both aspects of total distance and timeliness.
Keywords: emergency logistics networks; anti-bioterrorism systems; mixed-collaborative distribution; optimisation; bioterrorism; terrorism; anti-terrorism; forecasting models; emergency resources; epidemic diffusion rule; genetic algorithms; emergency management.
International Journal of Mathematics in Operational Research, 2011 Vol.3 No.2, pp.148 - 169
Available online: 06 Mar 2011Full-text access for editors Access for subscribers Purchase this article Comment on this article