وثيقة
Ant colony algorithm to solve a drone routing problem for hazardous waste collection
وكيل مرتبط
Harrath, Youssef , مؤلف مشارك
Kaabi, Jihene , مؤلف مشارك
عنوان الدورية
Arab Journal of Basic and Applied Sciences
العدد
2023, VOL. 30, NO. 1
الناشر
Taylor & Francis Group
تاريخ النشر
2023
اللغة
الأنجليزية
الموضوع
الملخص الإنجليزي
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.
المجموعة
المعرف
https://digitalrepository.uob.edu.bh/id/a293713d-498a-46c4-8456-83786f212392