RT Conference Proceedings
T1 More is not Always Better: 												Insights from a Massive Comparison of Meta-heuristic Algorithms over Real-Parameter Optimization Problems
A1 Del Ser, Javier
A1 Osaba, Eneko
A1 Martinez, Aritz D.
A1 Bilbao, Miren Nekane
A1 Poyatos, Javier
A1 Molina, Daniel
A1 Herrera, Francisco
AB Much controversy has been lately risen around the design and performance of modern bio-inspired optimization methods, in particular due to the alleged lack of algorithmic novelty in their definition with respect to traditional heuristic solvers. In this work we present a first attempt at shedding empirical evidence over this debate, for which results of a benchmark with unprecedented scales in terms of problems and algorithms are reported and discussed. Specifically, informed conclusions are held in what refers to the claimed superior performance of these bio-inspired solvers and their competitiveness when compared to competition-winning alternatives. Finally, we prove that the tailored selection of a subset of problems and techniques can unfairly bias the comparisons favoring any of such algorithms, ultimately arriving at illusory conclusions about their comparative performance.
PB Institute of Electrical and Electronics Engineers Inc.
SN 9781728190488
YR 2021
FD 2021
LK https://hdl.handle.net/11556/2172
UL https://hdl.handle.net/11556/2172
LA eng
NO Del Ser , J , Osaba , E , Martinez , A D , Bilbao , M N , Poyatos , J , Molina , D & Herrera , F 2021 , More is not Always Better : Insights from a Massive Comparison of Meta-heuristic Algorithms over Real-Parameter Optimization Problems . in 2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Proceedings . 2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Proceedings , Institute of Electrical and Electronics Engineers Inc. , 2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 , Orlando , United States , 5/12/21 . https://doi.org/10.1109/SSCI50451.2021.9660030
NO conference
NO Publisher Copyright: © 2021 IEEE.
NO The authors would like to thank the Basque Government for its support through the Consolidated Research Group MATHMODE (ref. IT1294-19), as well as EMAITEK and ELKARTEK grants.
DS TECNALIA Publications
RD 28 jul 2024