Abstract
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.
Highlights
Algorithm with Pitch Adjustment byMost real engineering problems are multi-objective in nature, since commonly they present several objective functions to be optimized that are compromised with each other, that is, the improvement of one produces the deterioration of another
The MOHS2, MOHS3 and multi-objective HS algorithm (MOHSg) algorithms are used to solve six problems reported in the literature [35,36], designated as P1 to P6, that are designed for measuring the performance of multi-objective optimization algorithms
A multi-objective Harmony Search (HS) algorithm (MOHSg) is proposed, whose fundamental contribution consists of the pitch adjustment based on the crowding distancing by genotype, that is, the crowding distancing that works in the search space
Summary
Daniel Molina-Pérez , Edgar Alfredo Portilla-Flores , Eduardo Vega-Alvarado * , Maria Bárbara Calva-Yañez and Gabriel Sepúlveda-Cervantes. Portilla-Flores, E.A.; Vega-Alvarado, E.; Calva-Yáñez, M.B.; Sepúlveda-Cervantes, G.
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