Solving the Multiple Traveling Salesman Problem Using Memetic Algorithm

Authors

  • Ahmad T. Al-Taani Department of Computer Sciences, Yarmouk University, Irbid, Jordan https://orcid.org/0000-0001-5900-6448
  • Lubna M. Al-Afifi Department of Computer Sciences, Yarmouk University, Irbid, Jordan

DOI:

https://doi.org/10.37256/aie.3120221206

Keywords:

hill-climbing algorithm, local search, shortest tour, population-based approach, hybrid metaheuristics, genetic algorithm

Abstract

The Multiple Traveling Salesman Problem (MTSP) is considered as an NP-complete problem due to the difficulty of finding the shortest tour between different cities with a set of constraints such as visiting each city once by one salesman. The solution tour represents the sum of all tours' costs performed by n salesmen. In this research, we propose a novel approach to find different solutions for various instances of MTSP based on a memetic algorithm using Genetic Algorithm (GA) and Hill-Climbing (HC) algorithm. The experimental results proved that the memetic approach achieved promising results i.e., minimum total tour compared to other existing approaches.

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Published

2022-01-17

How to Cite

1.
Al-Taani AT, Al-Afifi LM. Solving the Multiple Traveling Salesman Problem Using Memetic Algorithm. Artificial Intelligence Evolution [Internet]. 2022 Jan. 17 [cited 2024 Dec. 23];3(1):27-40. Available from: https://ojs.wiserpub.com/index.php/AIE/article/view/1206