Document
Ant colony algorithm to solve a drone routing problem for hazardous waste collection
Linked Agent
Harrath, Youssef , Author
Kaabi, Jihene , Author
Title of Periodical
Arab Journal of Basic and Applied Sciences
Issue published
2023, VOL. 30, NO. 1
Publisher
Taylor & Francis Group
Date Issued
2023
Language
English
Subject
English Abstract
Abstract :
Waste management issues are affecting the economic and environmental aspects of modern
societies. Thus, growing the interest of academic and industrial research and development
in optimizing the process of waste management. As these issues greatly impact human
health and environmental aspects and impose a threat, hazardous waste management
requires even much more attention. The problem studied in this research is a variant of the
vehicle routing problem using an unmanned aerial vehicle (UAV). The focus of this research
is on planning the routes for waste collection and disposal using a UAV. The aim is to collect
all the waste as early as possible respecting two constraints; the maximum flying and load
capacities of the UAV. A two-phase approach has been proposed to solve the investigated
problem. This approach is a hybridization of a developed heuristic (IMWMTT) and an Ant
Colony Optimization (ACO) algorithm. The experimental study showed that the hybrid
approach outperforms a recently published heuristic MWMTT for all tested instances of various sizes.
Member of
Identifier
https://digitalrepository.uob.edu.bh/id/a293713d-498a-46c4-8456-83786f212392