TY - JOUR ID - 91272 TI - Solving a multi-depot location-routing problem with heterogeneous vehicles and fuzzy travel times by a meta-heuristic algorithm JO - International Journal of Transportation Engineering JA - IJTE LA - en SN - 2322-259X AU - Zaker, Marzieh AU - Kheirkhah, Amir Saman AU - Tavakkoli-Moghaddam, Reza AD - M.Sc. Grad., Department of Industrial Engineering, Bu-Ali Sina University, Hamedan, Iran AD - Associate Professor, Department of Industrial Engineering, Bu-Ali Sina University, Hamedan, Iran AD - Professor, School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran Y1 - 2020 PY - 2020 VL - 7 IS - 4 SP - 415 EP - 431 KW - Multi-depot location-routing problem KW - Simultaneous pickup KW - and delivery KW - heterogeneous vehicles KW - Fuzzy Travel Time KW - meta-heuristic algorithm DO - 10.22119/ijte.2018.108175.1377 N2 - A capacitated location-routing problem (CLRP) is one of the new areas of research in distribution management. It consists of two problems; locating of facilities and routing of the vehicle with a specific capacity. The purpose of the CLRP is to open a set of stores, allocate customers to established deposits, and then design vehicle tours in order to minimize the total cost. In this paper, a new mathematical programming model for multi-depot location-routing problems is considered. This model considers heterogeneous vehicles and fuzzy travel times, which are innovative and practical limitations compared to the previous studies (e.g., simultaneous pickup and delivery). This makes the model close to real-world situations. After modeling, the fuzzy model is changed to a deterministic model by credibility theory. Since this problem belongs to a class of NP-hard ones because of its computational complexity, it is impossible to find the optimal solution in reasonable time. Therefore, a particle swarm optimization algorithm is proposed and designed to solve the presented model. To show the efficiency of the proposed PSO, its results are compared with the optimal solutions obtained by an exact method embedded in the optimization software. Furthermore, the proposed PSO is able to solve medium- and large-sized problem efficiently. UR - http://www.ijte.ir/article_91272.html L1 - http://www.ijte.ir/article_91272_81384634a80eb64f61dfde70c1b5aee2.pdf ER -