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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Computer Science
Mohammed Essaid Riffi
University of Chouaib Doukkali
Computer Science & IT Electrical & Electronics Engineering

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Parallel hybrid chicken swarm optimization for solving the quadratic assignment problem Soukaina Cherif Bourki Semlali; Mohammed Essaid Riffi; Fayçal Chebihi
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (487.801 KB) | DOI: 10.11591/ijece.v9i3.pp2064-2074

Abstract

In this research, we intend to suggest a new method based on a parallel hybrid chicken swarm optimization (PHCSO) by integrating the constructive procedure of GRASP and an effective modified version of Tabu search. In this vein, the goal of this adaptation is straightforward about the fact of preventing the stagnation of the research. Furthermore, the proposed contribution looks at providing an optimal trade-off between the two key components of bio-inspired metaheuristics: local intensification and global diversification, which affect the efficiency of our proposed algorithm and the choice of the dependent parameters. Moreover, the pragmatic results of exhaustive experiments were promising while applying our algorithm on diverse QAPLIB instances . Finally, we briefly highlight perspectives for further research.
Memetic chicken swarm algorithm for job shop scheduling problem Soukaina Cherif Bourki Semlali; Mohammed Essaid Riffi; Fayçal Chebihi
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (269.568 KB) | DOI: 10.11591/ijece.v9i3.pp2075-2082

Abstract

This paper presents a Memetic Chicken swarm optimization (MeCSO) to solve job shop scheduling problem (JSSP). The aim is to find a better solution which minimizes the maximum of the completion time also called Makespan. In this paper, we adapt the chicken swarm algorithm which take into consideration the hierarchical order of chicken swarm while seeking for food. Moreover, we integrate 2-opt method to improve the movement of the rooster. The new algorithm is applied on some instances of ORLibrary. The empirical results show the forcefulness of MeCSO comparing to other metaheuristics from literature in term of run time and quality of solution.
Discrete Chicken Swarm Optimization for the Quadratic Assignment Problem Soukaina Cherif Bourki Semlali; Mohammed Essaid Riffi; Fayçal Chebihi
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp925-935

Abstract

The main objective of our research is to improve an adaptation of the chicken swarm optimization algorithm (CSO) to solve the quadratic assignment problem, which is a well-known combinatorial optimization problem. The new approach is based on the CSO without using a local search, the CSO-QAP is a stochastic method inspired from the behavior of chickens in swarm while searching for food. The experiments are performed on a set of 56 benchmark QAPLIB instances. To prove the robustness of our algorithm a comparative analysis is done with the known metaheuristic of Genetic algorithm based on SCX. The average percentage of error to get the best Known solution in our proposed work with the results obtained by applying a simple genetic algorithm using sequential constructive crossover for the quadratic assignment problem. The results show the effectiveness of the proposed CSO-QAP to solve the Quadratic assignment problem in term of time and quality of solutions. The proposed adaptation can be further applied by using a local search strategy to solve the same problem or another combinatorial problem.
Co-Authors Fayçal Chebihi Soukaina Cherif Bourki Semlali