@inbook{8d2f257ff1d5454181604017e105fbbf,
title = "High-performance architecture for the modified NSGA-II",
abstract = "NSGA-II is one of the most popular algorithms for solving Multiobjective Optimization Problems. It has been used to solve different real-world optimization problems; however, NSGA-II has been criticized for its high computational cost and bad performance on applications with more than two objective functions. In this paper, we propose a high-performance architecture for the NSGA-II using parallel computing, for evaluation functions and genetic operators. In the proposed architecture, the Mishra Fast Algorithm for finding the Non Dominated Set was used. In this paper, we propose a modification in the sorting process for the NSGA-II that improves the distribution of the solutions in the Pareto front. Results for five different test functions using distinct crossover and mutation operators to test performance are presented.",
keywords = "Genetic algorithm, Multi-objective optimization, NSGA - II, Pareto Optimal",
author = "Josu{\'e} Dom{\'i}nguez and Oscar Montiel-Ross and Roberto Sep{\'u}lveda",
year = "2013",
doi = "10.1007/978-3-642-35323-9_13",
language = "Ingl{\'e}s",
isbn = "9783642353222",
series = "Studies in Fuzziness and Soft Computing",
publisher = "Springer Verlag",
pages = "321--341",
booktitle = "Soft Computing Applications in Optimization, Control, and Recognition",
address = "Alemania",
}