A congested capacitated multi-level fuzzy facility location problem: An efficient drone delivery system

被引:66
|
作者
Shavarani, Seyed Mahdi [1 ]
Mosallaeipour, Sam [2 ]
Golabi, Mahmoud [3 ]
Izbirak, Gokhan [4 ]
机构
[1] Univ Manchester, Alliance Manchester Business Sch, Manchester, Lancs, England
[2] Nhl Stenden Univ Appl Sci, Acad Technol & Innovat, Tech Business Sch Tech Bedrijfskunde, Leeuwarden, Netherlands
[3] Girne Amer Univ, Dept Ind Engn, Girne, Turkey
[4] Eastern Mediterranean Univ, Dept Ind Engn, Famagusta, Turkey
关键词
ALLOCATION PROBLEM; ROBUST SOLUTIONS; SELECTION; MODELS; OPTIMIZATION; PRICE;
D O I
10.1016/j.cor.2019.04.001
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Online retailers invest an enormous amount of funds in delivering products to customers. In recent years, these delivery costs have increased as a result of changes in fuel costs, which has brought new challenges to retailers in terms of offering competitive prices. Many retailers have begun to utilize a drone-based aerial delivery system as an alternative solution to overcome the problems related to the high transportation costs and traffic jams in large cities. This study provides a mathematical model for minimizing the total costs of the aerial delivery system concerned with refuel stations, warehouses, drone procurement, and transportation. The waiting time of the customers is restricted based on the M/G/K queueing system. The fuel stations and warehouses are the main components of the network. The demand (occurring at the lowest level) is ultimately satisfied via launch stations (the network's highest level). Refuel stations support drones along their long routes between the launch stations and demand points. To account for the different levels of the facilities, a multi-level facility location approach is utilized. Moreover, the non-deterministic nature of the problem is tackled using fuzzy variables. The ultimate mathematical model is a congested fuzzy capacitated multi-level facility location problem that is solved by the possibilistic approach. (C) 2019 Elsevier Ltd. All rights reserved.
引用
收藏
页码:57 / 68
页数:12
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