A Fast Elitist Non-Dominated Sorting Genetic Algorithm for Multi-Objective Optimization: NSGA-II

A Fast Elitist Non-Dominated Sorting Genetic Algorithm for Multi-Objective Optimization: NSGA-II (2000)

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by Kalyanmoy Deb , Samir Agrawal , Amrit Pratap , T Meyarivan

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Datum	Value	Source
TITLE	A Fast Elitist Non-Dominated Sorting Genetic Algorithm for Multi-Objective Optimization: NSGA-II	INFERENCE
AUTHOR NAME	Kalyanmoy Deb	user correction - Legacy Corrections
AUTHOR AFFIL	Kanpur Genetic Algorithms Laboratory (KanGAL); Indian Institute of Technology Kanpur	user correction - Legacy Corrections
AUTHOR ADDR	Kanpur, PIN 208 016, India	user correction - Legacy Corrections
AUTHOR NAME	Samir Agrawal	user correction - Legacy Corrections
AUTHOR NAME	Amrit Pratap	user correction - Legacy Corrections
AUTHOR NAME	T Meyarivan	user correction - Legacy Corrections
AUTHOR AFFIL	deb,samira,apratap,mary¡	user correction - Legacy Corrections
ABSTRACT	Multi-objective evolutionary algorithms which use non-dominated sorting and sharing have been mainly criticized for their (i) -4 computational complexity (where is the number of objectives and is the population size), (ii) non-elitism approach, and (iii) the need for specifying a sharing parameter. In this paper, we suggest a non-dominated sorting based multi-objective evolutionary algorithm (we called it the Non-dominated Sorting GA-II or NSGA-II) which alleviates all the above three difficulties. Specifically, a fast non-dominated sorting approach with computational complexity is presented. Second, a selection operator is presented which creates a mating pool by combining the parent and child populations and selecting the best (with respect to fitness and spread) solutions. Simulation results on five difficult test problems show that the proposed NSGA-II is able to find much better spread of solutions in all problems compared to PAES---another elitist multi-objective EA which pays special attention towards creating a diverse Pareto-optimal front. Because of NSGA-II's low computational requirements, elitist approach, and parameter-less sharing approach, NSGA-II should find increasing applications in the years to come.	user correction - Legacy Corrections
YEAR	2000	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	849--858	INFERENCE
CITATIONS	0 found	ParsCit 1.0