Abdesslem Layeb

Work place: MISC Lab, Computer science department, Mentouri university of Constantine, Constantine, Algeria

E-mail: layeb@umc.edu.dz

Website: https://orcid.org/0000-0002-6553-8253

Research Interests: Formal Methods, Theoretical Computer Science, Computer systems and computational processes, Bioinformatics

Biography

Abdesslem Layeb is Senior Lecturer in the department of computer science at the University of Constantine. He received his PhD degree in computer science from the University Mentouri of Constantine, Algeria. Dr. Layeb is interested to the combinatorial optimization methods and its application to solve several problems from different domains like Bioinformatics, imagery, formal methods. Dr. Layeb has many publications in theoretical computer science, bioinformatics, and formal methods.

Author Articles
A Multi-objective Binary Cuckoo Search for Bi-criteria Knapsack Problem

By Abdesslem Layeb Nesrine Lahouesna Bouchra Kireche

DOI: https://doi.org/10.5815/ijieeb.2013.04.02, Pub. Date: 8 Oct. 2013

Cuckoo Search (CS) is one of the most recent population-based metaheuristics. CS algorithm is based on the cuckoo’s behavior and the mechanism of Lévy flights. The Binary Cuckoo Search algorithm (BCS) is new discrete version used to solve binary optimization problem based on sigmoid function. In this paper, we propose a new cuckoo search for binary multiobjective optimization. Pareto dominance is used to find optimal pareto solutions. Computational results on some bi-criteria knapsack instances show the effectiveness of the proposed algorithm and its ability to achieve good quality solutions.

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A Novel Quantum Inspired Cuckoo Search Algorithm for Bin Packing Problem

By Abdesslem Layeb Seriel Rayene Boussalia

DOI: https://doi.org/10.5815/ijitcs.2012.05.08, Pub. Date: 8 May 2012

The Bin Packing Problem (BPP) is one of the most known combinatorial optimization problems. This problem consists to pack a set of items into a minimum number of bins. There are several variants of this problem; the most basic problem is the one-dimensional bin packing problem (1-BPP). In this paper, we present a new approach based on the quantum inspired cuckoo search algorithm to deal with the 1-BPP problem. The contribution consists in defining an appropriate quantum representation based on qubit representation to represent bin packing solutions. The second contribution is proposition of a new hybrid quantum measure operation which uses first fit heuristic to pack no filled objects by the standard measure operation. The obtained results are very encouraging and show the feasibility and effectiveness of the proposed approach.

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A Novel GRASP Algorithm for Solving the Bin Packing Problem

By Abdesslem Layeb Sara Chenche

DOI: https://doi.org/10.5815/ijieeb.2012.02.02, Pub. Date: 8 Apr. 2012

The Bin Packing Problem (BPP) is one of the most known combinatorial optimization problems. This problem consists in packing a set of items into a minimum number of bins. There are several variants of this problem; the most basic problem is the one-dimensional bin packing problem (1-BPP). In this paper, we present a new approach based on the GRASP procedure to deal with the1-BPP problem. The first GRASP phase is based on a new random heuristics based on hybridization between First Fit and Best Fit heuristics. The second GRASP phase is based on Tabu search algorithm used for the enhancement of the solutions found in the first phase. The obtained results are very encouraging and show the feasibility and effectiveness of the proposed approach.

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