Authors: Lamiche Chaabane
Addresses: Computer Science Department, University of M'sila, BP. 166 M'sila 28000, Algeria
Abstract: In this research study, we aim to propose a novel cooperative approach called dynamic simulated particle swarm optimisation (DSPSO) which is based on metaheuristics and the pairwise dynamic programming (DP) procedure to find an approximate solution for the multiple-sequence alignment (MSA) problem. The developed approach applies the particle swarm optimisation (PSO) algorithm to discover the search space globally and the simulated annealing (SA) technique to improve the population leader quality in order to overcome local optimum problem. After that the dynamic programming technique is integrated as an improver mechanism in order to improve the worst solution quality and to increase the convergence speed of the proposed approach. Simulation results on BAliBASE benchmarks have shown the potent of the proposed method to produce good quality alignments comparing to those given by other literature existing methods.
Keywords: cooperative approach; multiple-sequence alignment; MSA; DSPSO; particle swarm optimisation; PSO; SA; DP; BAliBASE benchmarks.
International Journal of Data Mining, Modelling and Management, 2021 Vol.13 No.1/2, pp.1 - 16
Received: 13 Aug 2018
Accepted: 05 Mar 2019
Published online: 09 Feb 2021 *