Title: Bio-inspired parameter-less heuristic for NP-hard (complete) discrete problems

Authors: Manal Zettam

Addresses: Informatics, Systems and Optimization Laboratory, Department of Computer Science, Faculty of Science, Ibn Tofail University, Kenitra, Morocco

Abstract: In this article, a bio-inspired parameter-less heuristic employs a path-relinking approach coupled with a local search instead of moving alternatives within the search space. In addition, a mean solution has assured the exploration and exploitation phases. The proposed bio-inspired parameter-less heuristic has been compared to ZODIAC, GRAFICS, WFA-water flow, EA-evolutionary algorithm, GRASP, GATSP, HGA-hybrid genetic algorithm, GA-genetic algorithm, HGDE-differential evolution algorithm, ACO-ant colony optimisation, HGGA-grouping genetic algorithm, SACF-simulated annealing algorithm, GAA-genetic algorithm, SCF-BMCF-hybrid heuristic algorithm, EnGGA-enhanced grouping genetic algorithm, SA - simulated annealing, SA_YLL - simulated annealing with variable on set of benchmarks. The comparative study shows that the proposed heuristic performs well on 26 benchmarks.

Keywords: NP-complete problem; bio-inspired heuristic; path-relinking; parameter-less heuristic.

DOI: 10.1504/IJBIC.2020.108998

International Journal of Bio-Inspired Computation, 2020 Vol.16 No.1, pp.33 - 43

Accepted: 19 Jan 2020
Published online: 14 Aug 2020 *

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