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

Nizar Rokbani,Pavel Kromer,Adel M Alimi,Ikram Twir

doi:10.4018/ijsda.2020070104

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.

Highlights

The advent of self-driving cars, intelligent transportation systems, and internet of things devices routing challenges, recalled the interest in combinatorial optimization problems, COP
A new hierarchical hybrid method is proposed as a hybridization of Ant Colony Optimization (ACO), Firefly Algorithm (FA), and local search (AS-FA-Ls)
Using the FA as in (Kumbharana & Pandey, 2013) and (Ariyantne et al, 2016), The AS-FA-Ls, give a better result for berlin 52 and Kroa 100: for the remaining of the test instances AS-FA-Ls returned fair solutions for all test benches used in this study especially for berlin52, st70 and kroA100, see Table 3 for detailed results

Summary

Introduction

The advent of self-driving cars, intelligent transportation systems, and internet of things devices routing challenges, recalled the interest in combinatorial optimization problems, COP. 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).

Results

Conclusion