The TSP-D, a version of the travelling salesman problem in drone-based delivery systems, is the subject of this study. The TSP-D is a combinatorial optimization problem in which a truck and a drone work together to deliver packages to clients in the shortest time possible. Because determining the best answer is NP-hard, the number of problems that can be solved optimally is restricted. As a result, metaheuristics are employed to tackle the issue. Metaheuristics are adaptive and intelligent algorithms that have been proven to work in a variety of situations. This paper provides a hybrid meta-heuristic solution to the TSP-D issue, where the answer is based on the Concorde TSP solver's optimal TSP solution. The greedy, randomised adaptive search technique (GRASP) with two local search alternatives is then used to find the delivery routes for the truck and the drone. The application of self-adaptive selection when searching the neighbourhood in GRASP is the work's key contribution. The suggested method was evaluated on 200 cases from the publicly available "Instances of TSP with Drone" benchmark with various parameters. The results were compared to cutting-edge algorithms. In terms of tour duration, nonparametric statistical tests revealed that the proposed strategy is equivalent to rival algorithms (p = 0:074). When the drone and truck are travelling at the same speed ((alpha) = 1), the proposed method performs better or similarly.
Author(S) Details
Sarab AlMuhaideb
Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh 11362, Saudi Arabia.
Taghreed Alhussan
Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh 11362, Saudi Arabia.
Sara Alamri
Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh 11362, Saudi Arabia.
Yara Altwaijry
Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh 11362, Saudi Arabia.
Lujain Aljarbou
Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh 11362, Saudi Arabia.
Haifa Alrayes
Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh 11362, Saudi Arabia.
View Book:- https://stm.bookpi.org/RAMRCS-V5/article/view/4977
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