Title: Multi-agent simulated annealing algorithm based on differential perturbation for protein structure prediction problems

Authors: Yiwen Zhong; Juan Lin; Qingliang Du; Limei Wang

Addresses: College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou 350002, China ' College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou 350002, China ' College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou 350002, China ' College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou 350002, China

Abstract: Simulated annealing (SA) algorithm is extremely slow in convergence, and the implementation and efficiency of parallel SA algorithms are typically problem-dependent. To overcome such intrinsic limitations, this paper presents a multi-agent SA (MSA) algorithm to address protein structure prediction problems based on the 2D off-lattice model. Inspired by the learning ability of the mutation operators in differential evolution algorithm, three differential perturbation (DP) operators are defined to generate candidate solutions collaboratively. This paper also analyses the effect of different sampling grain, which determines how many dimensions will be perturbed when a candidate solution is generated. The proposed MSA algorithm can achieve better intensification ability by taking advantage of the learning ability from DP operators, which can adjust its neighbourhood structure adaptively. Simulation experiments were carried on four artificial Fibonacci sequences, and the results show that the performance of MSA algorithm is promising.

Keywords: MAS; multi-agent systems; agent-based systems; simulated annealing; differential evolution; differential perturbation; sampling grain; PSP; protein structure prediction; off-lattice modelling; Fibonacci sequences; bioinformatics.

DOI: 10.1504/IJCAT.2015.069330

International Journal of Computer Applications in Technology, 2015 Vol.51 No.3, pp.164 - 172

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 11 May 2015 *

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