%0 Journal Article
%T A fuzzy two-stage capacitated continuous p-centmedian vehicle routing problem: A self-adaptive evolutionary
%J International Journal of Transportation Engineering
%I Tarrahan Parseh Transportation Research Institute
%Z 2322-259X
%A Aghamohamadi, Soroush
%A Tavakkoli-Moghaddam, Reza
%A Rahimi, Yaser
%A Memari, Pedram
%D 2019
%\ 10/01/2019
%V 7
%N 2
%P 217-232
%! A fuzzy two-stage capacitated continuous p-centmedian vehicle routing problem: A self-adaptive evolutionary
%K p-Median and p-Center problem
%K Capacitated vehicle routing
%K Taguchi method
%K Fuzzy set
%K Differential evolution
%R 10.22119/ijte.2018.105564.1376
%X In this paper, a two-stage continuous p-center and p-median (namely p-centmedian) problem is developed. In the first step, a location problem is studied to compare the differences between the p-center and p-median by considering facility disruption. P-center problems are common in emergency situations with aim of minimizing the maximum distance between the facilities and costumers, while p-median problem aim is to minimize the total spent distance. Moreover, an integer linear programming is developed to deal with a time-window multi-depot capacitated vehicle routing problem in order to optimize the flows between facilities. This paper compares the mentioned p-center and p-median effects along with the vehicle routing problem as a two-step integrate problem. Since both steps are NP-hard, to deal with the problem in both stages a possibilistic programming, fuzzy single-objective programming is developed and solved by an efficient algorithm, namely self-adaptive differential evolution algorithm. Considering demand as a fuzzy parameter is an important factor and makes the problem more realistic, this feature is more considerable in emergency situations such as p-center problems. To improve the performance of results, the Taguchi method is used. In order to validate the results of the mentioned algorithms of small-sized test problems are compared with GAMS, also other valid meta-heuristics are developed to be compared with the proposed algorithm in large-sized problems. The results show the capability of algorithm to generate near-optimal solutions. Also, the results demonstrate the p-median problem is more volatile against variation in the parameters while the p-center problem is more expensive.
%U http://www.ijte.ir/article_69686_6be6cb6e3487b1c6711e6677cd5c74a0.pdf