%0 Journal Article
%T A cluster-based emergency vehicle routing problem in disaster with reliability
%J Scientia Iranica
%I Sharif University of Technology
%Z 1026-3098
%A Gharib, Zahra
%A Bozorgi-Amiri, Ali
%A Tavakkoli-Moghaddam, Reza
%A Najafi, Esmaeil
%D 2018
%\ 08/01/2018
%V 25
%N 4
%P 2312-2330
%! A cluster-based emergency vehicle routing problem in disaster with reliability
%K disaster
%K Relief distribution
%K Vehicle routing problem
%K Clustering
%K Reliability
%K multi-objective meta-heuristics
%R 10.24200/sci.2017.4450
%X In the event of natural disasters, relief distribution is the most challenging problem of emergency transportation. What is important in response to disaster is victimsâ€™ relief in disaster areas with the quick distribution of vital commodity. In this regard, damage to infrastructure (e.g., roads) can make trouble in designing a distribution network. So, this paper considers a problem using a three-stage approach. In the first stage, pre-processing of model inputs is done through an artificial neural fuzzy inference system (ANFIS) followed by investigating the safest route for each cluster using of decision-making techniques and graph theory. In the second stage, a heterogeneous multi-depots multi-mode vehicle routing problem is formulated for minimizing the transportation time and maximize the reliability. Finally, since the routing problem is NP-hard, two multi-objective meta-heuristic algorithms, namely non-dominated sorting genetic algorithm (NSGA-II) and multi-objective firefly algorithm (MOFA), are proposed to obtain the optimal solution and compared their performance through a set of randomly generated test problems. The results show that for this routing problem, the MOFF gives better solutions in comparison to NSGA-II and performs well in terms of accuracy and solution time.
%U https://scientiairanica.sharif.edu/article_4450_caeea5190fbcd2e9d58fbdcb33557f73.pdf