@inproceedings{7bf1ee8b5fbc4864b9bd8d76d59ff0f0,
title = "Population size matters: Rigorous runtime results for maximizing the hypervolume indicator",
abstract = "Using the hypervolume indicator to guide the search of evolutionary multi-objective algorithms has become very popular in recent years. We contribute to the theoretical understanding of these algorithms by carrying out rigorous runtime analyses. We consider multi-objective variants of the problems OneMax and LeadingOnes called OneMinMax and LOTZ, respectively, and investigate hypervolume-based algorithms with population sizes that do not allow coverage of the entire Pareto front. Our results show that LOTZ is easier to optimize than OneMinMax for hypervolume-based evolutionary multi-objective algorithms which is contrary to the results on their single-objective variants and the well-studied (1+1) EA.",
keywords = "Multi-objective Optimization, Runtime Analysis, Theory",
author = "Nguyen, {Anh Quang} and Sutton, {Andrew M.} and Frank Neumann",
year = "2013",
doi = "10.1145/2463372.2463564",
language = "English (US)",
isbn = "9781450319638",
series = "GECCO 2013 - Proceedings of the 2013 Genetic and Evolutionary Computation Conference",
pages = "1613--1620",
booktitle = "GECCO 2013 - Proceedings of the 2013 Genetic and Evolutionary Computation Conference",
note = "2013 15th Genetic and Evolutionary Computation Conference, GECCO 2013 ; Conference date: 06-07-2013 Through 10-07-2013",
}