Paper Info
Title
A Hybrid Hierarchical Heuristic-Aco With Local Search Applied To Travelling Salesman Problem, As-Fa-Ls
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.
Year
DOI
Venue
2020
10.4018/IJSDA.2020070104
INTERNATIONAL JOURNAL OF SYSTEM DYNAMICS APPLICATIONS
Keywords
DocType
Volume
ACO, Ant Supervised By FA ASFA, ANT Supervised By Firefly With Local Search, AS-FA-Ls, FA, Firefly Algorithm, Local Search, Travelling: Salesman Problem
Journal
9
Issue
ISSN
Citations 
3
2160-9772
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Nizar Rokbani1296.80
Krömer Pavel233059.99
Ikram Twir300.34
Mohamed Adel Alimi41947217.16