RT Conference Proceedings
T1 Hybridizing differential evolution and novelty search for multimodal optimization problems
A1 Martinez, Aritz D.
A1 Fister, Iztok
A1 Osaba, Eneko
A1 Fister, Iztok
A1 Oregi, Izaskun
A1 Ser, Javier Del
AB Multimodal optimization has shown to be a complex paradigm underneath real-world problems arising in many practical applications, with particular prevalence in physics-related domains. Among them, a plethora of cases within the computational design of aerospace structures can be modeled as a multimodal optimization problem, such as aerodynamic optimization or airfoils and wings. This work aims at presenting a new research direction towards efficiently tackling this kind of optimization problems, which pursues the discovery of the multiple (at least locally optimal) solutions of a given optimization problem. Specifically, we propose to exploit the concept behind the so-called Novelty Search mechanism and embed it into the self-adaptive Differential Evolution algorithm so as to gain an increased level of controlled diversity during the search process. We assess the performance of the proposed solver over the well-known CEC'2013 suite of multimodal test functions. The obtained outcomes of the designed experimentation supports our claim that Novelty Search is a promising approach for heuristically addressed multimodal problems.
PB Association for Computing Machinery, Inc
SN 9781450367486
YR 2019
FD 2019-07-13
LK https://hdl.handle.net/11556/2283
UL https://hdl.handle.net/11556/2283
LA eng
NO Martinez , A D , Fister , I , Osaba , E , Fister , I , Oregi , I & Ser , J D 2019 , Hybridizing differential evolution and novelty search for multimodal optimization problems . in GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion . GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion , Association for Computing Machinery, Inc , pp. 1980-1989 , 2019 Genetic and Evolutionary Computation Conference, GECCO 2019 , Prague , Czech Republic , 13/07/19 . https://doi.org/10.1145/3319619.3326799
NO conference
NO Publisher Copyright: © 2019 Association for Computing Machinery.
NO The authors would like to thank the Basque Government for its funding support through the EMAITEK program.
DS TECNALIA Publications
RD 28 jul 2024