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Título del libro: 2016 Ieee Congress On Evolutionary Computation (cec)
Título del capítulo: p-MOEA: A new multi-objective evolutionary algorithm based on the p indicator

Autores UNAM:
ADRIANA MENCHACA MENDEZ; CARLOS IGNACIO HERNANDEZ CASTELLANOS;
Autores externos:

Idioma:
Inglés
Año de publicación:
2016
Palabras clave:

Mobility aids for blind persons; Surface reconstruction; Fitness assignment; Hypervolume indicators; Multi objective evolutionary algorithms; Nondominated solutions; Objective functions; Reference set; Selection scheme; Standard test functions; Evolutionary algorithms


Resumen:

In this paper, we propose a new selection scheme for Multi-Objective Evolutionary Algorithms (MOEAs) based on the ? indicator. Our new selection scheme is incorporated into a MOEA giving rise to the ' ?-MOEA.' Perhaps, one of the most important disadvantages of MOEAs based on ? is the definition of the reference set. In this work, we propose to create a reference set at each generation using e-dominance and the set of nondominated solutions found so far. Our new selection scheme uses two different techniques to select solutions according to the modified generational distance indicator or the modified inverted generational distance indicator. Our proposed p-MOEA is validated using standard test functions taken from the specialized literature, having three to six objective functions and it is compared with respect to two well-known MOEAs: MOEA/D using Penalty Boundary Intersection (PBI), which is based on decomposition, and SMS-EMOA-HYPE (a version of SMS-EMOA that uses a fitness assignment scheme based on the use of an approximation of the hypervolume indicator). © 2016 IEEE.


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