Particle Swarm Optimization with Tabu Search Algorithm (PSO-TS) Applied to Multiple Sequence Alignment Problem
Advances in Multidisciplinary Medical Technologies â Engineering, Modeling and Findings, Springer International Publishing, (November 2020)DOI: 10.1007/978-3-030-57552-6_8
Abstract
In the bioinformatics realm, multiple sequence alignment (MSA) is an NP-hard problem. Nature-inspired methodologies configure potent tools to outsmart conventional optimization tactics to encounter an approximate solution for MSA. This investigatory work brings in a novel hybrid algorithm termed PSO-TS for solving the MSA problem. The PSO-TS employs the particle swarm optimization (PSO) procedure to explore the search space better, but the local optimum limit may hinder it. For that, the tabu search (TS) procedure ameliorates the global best solution quality. Numerical experimental outcomes on some BaliBASE benchmark instances confirmed the capability of the PSO-TS approach to producing better by-products while comparing it to other established literary works.