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A Hybrid Hierarchical Heuristic-ACO With Local Search Applied to Travelling Salesman Problem, AS-FA-Ls

A Hybrid Hierarchical Heuristic-ACO With Local Search Applied to Travelling Salesman Problem, AS-FA-Ls

Nizar Rokbani, Pavel Kromer, Ikram Twir, Adel M. Alimi
Copyright: © 2020 |Volume: 9 |Issue: 3 |Pages: 16
ISSN: 2160-9772|EISSN: 2160-9799|EISBN13: 9781799807957|DOI: 10.4018/IJSDA.2020070104
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MLA

Rokbani, Nizar, et al. "A Hybrid Hierarchical Heuristic-ACO With Local Search Applied to Travelling Salesman Problem, AS-FA-Ls." IJSDA vol.9, no.3 2020: pp.58-73. http://doi.org/10.4018/IJSDA.2020070104

APA

Rokbani, N., Kromer, P., Twir, I., & Alimi, A. M. (2020). A Hybrid Hierarchical Heuristic-ACO With Local Search Applied to Travelling Salesman Problem, AS-FA-Ls. International Journal of System Dynamics Applications (IJSDA), 9(3), 58-73. http://doi.org/10.4018/IJSDA.2020070104

Chicago

Rokbani, Nizar, et al. "A Hybrid Hierarchical Heuristic-ACO With Local Search Applied to Travelling Salesman Problem, AS-FA-Ls," International Journal of System Dynamics Applications (IJSDA) 9, no.3: 58-73. http://doi.org/10.4018/IJSDA.2020070104

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Abstract

The combinatorial optimization problem is attracting research because they have a wide variety of applications ranging from route planning and supply chain optimization to industrial scheduling and the IoT. Solving such problems using heuristics and bio-inspired techniques is an alternative to exact solutions offering acceptable solutions at fair computational costs. In this article, a new hierarchical hybrid method is proposed as a hybridization of Ant Colony Optimization (ACO), Firefly Algorithm (FA), and local search (AS-FA-Ls). The proposed methods are compared to similar techniques on the traveling salesman problem, (TSP). ACO is used in a hierarchical collaboration schema together with FA which is used to adapt ACO parameters. A local search strategy is used which is the 2 option method to avoid suboptimal solutions. A comparative review and experimental investigations are conducted using the TSP benchmarks. The results showed that AS-FA-Ls returned better results than the listed works in the following cases: berlin52, st70, eil76, rat99, kroA100, and kroA200. Computational investigations allowed determining a set of recommended parameters to be used with ACO for the TSP instances of the study.