Name
Title | ||
|---|---|---|
Hybridizing differential evolution and novelty search for multimodal optimization problems. |
Abstract | ||
|---|---|---|
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.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3319619.3326799 | GECCO |
Keywords | Field | DocType |
Multimodal Optimization, Novelty Search, Differential Evolution | Computer science,Differential evolution,Artificial intelligence,Novelty,Optimization problem,Machine learning | Conference |
ISBN | Citations | PageRank |
978-1-4503-6748-6 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aritz D. Martinez | 1 | 3 | 3.75 |
| eneko | 2 | 258 | 33.50 |
| Izaskun Oregi | 3 | 15 | 3.07 |
| Iztok Fister Jr. | 4 | 447 | 35.34 |
| Iztok Fister | 5 | 552 | 39.46 |
| Javier Del Ser | 6 | 712 | 87.90 |