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

Abstract

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 nondeterministic 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.

Last-mile delivery concepts: a survey from an operational research perspective

“…They provide a MIP and a heuristic solution approach to maximize the weighted number of covered customers for a limited number of charging stations and a discrete set of potential locations. A similar setting is investigated by Shavarani et al (2019), who propose a fuzzy approach. The uncertainty with regard to the customer locations that are to be visited, which is typically unknown during long-term location planning, is certainly an aspect that deserves more attention.…”

Scheduling of a Parcel Delivery System Consisting of an Aerial Drone Interacting with Public Transportation Vehicles

“…In this paper, a drone only delivers to one customer and the impact of the payload is also accounted. The reference [24] addresses the problem of positioning warehouses as well as refuel stations.…”

“…Following the second model, some publications have considered the facility location problem under the context of drone delivery to extend the delivery area [23,24]. Clearly, one disadvantage of this method is the investment in constructing the new facilities.…”

“…The current paper also focuses on addressing this shortcoming. Unlike [23,24] to place more facilities, we introduce the idea of drone-vehicle collaboration [25,26]. Here, the vehicle refers to the public transportation vehicles.…”

Assignment of Medical Staff to Operating Rooms in Disaster Preparedness: A Novel Stochastic Approach

“…As described by Mangano [49], GAs provide large-scale problems with solutions that might not otherwise be achievable in a lifetime. Inspired by the evolution of a species through generations in nature, GA was developed by John Holland (1970's) and has been utilized in many studies since [50]- [54].…”