A Novel Multi-Objective Harmony Search Algorithm with Pitch Adjustment by Genotype

Autor: Daniel Molina-Pérez, Edgar Alfredo Portilla-Flores, Eduardo Vega-Alvarado, Maria Bárbara Calva-Yañez, Gabriel Sepúlveda-Cervantes
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Applied Sciences, Vol 11, Iss 19, p 8931 (2021)
Druh dokumentu: article
ISSN: 11198931
2076-3417
DOI: 10.3390/app11198931
Popis: In this work, a new version of the Harmony Search algorithm for solving multi-objective optimization problems is proposed, MOHSg, with pitch adjustment using genotype. The main contribution consists of adjusting the pitch using the crowding distance by genotype; that is, the distancing in the search space. This adjustment automatically regulates the exploration–exploitation balance of the algorithm, based on the distribution of the harmonies in the search space during the formation of Pareto fronts. Therefore, MOHSg only requires the presetting of the harmony memory accepting rate and pitch adjustment rate for its operation, avoiding the use of a static bandwidth or dynamic parameters. MOHSg was tested through the execution of diverse test functions, and it was able to produce results similar or better than those generated by algorithms that constitute search variants of harmonies, representative of the state-of-the-art in multi-objective optimization with HS.
Databáze: Directory of Open Access Journals