Generalized Differential Evolution for Numerical and Evolutionary Optimization
| Autor: | Saku Kukkonen, Carlos A. Coello Coello |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
Mathematical optimization Meta-optimization Computer science Constrained optimization 02 engineering and technology Multi-objective optimization Nonlinear programming Constraint (information theory) 03 medical and health sciences 030104 developmental biology Differential evolution 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing CMA-ES Evolution strategy |
| Zdroj: | Studies in Computational Intelligence ISBN: 9783319440026 NEO |
| DOI: | 10.1007/978-3-319-44003-3_11 |
| Popis: | This chapter is about Generalized Differential Evolution (GDE), which is a general purpose optimizer for global nonlinear optimization. It is based on Differential Evolution (DE), which has been gaining popularity because of its simplicity and good observed performance. GDE extends DE for problems with several objectives and constraints. The chapter concentrates on describing different development phases and performance of GDE but it also contains a brief listing of other multi-objective DE approaches. Ability to solve multi-objective problems is mainly discussed, but constraint handling and the effect of control parameters are also covered. It is found that the latest GDE version is effective and efficient for solving constrained multi-objective problems having different types of decision variables. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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