Using competitive population evaluation in a differential evolution algorithm for dynamic environments

DOI10.1016/j.ejor.2011.08.031zbMath1244.90246OpenAlexW1975540119MaRDI QIDQ439447

Mathys C. Du Plessis, Andries P. Engelbrecht

Publication date: 16 August 2012

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/2263/19181

zbMATH Keywords

optimizationevolutionary computationdifferential evolution\texttt{DynDE}dynamic environments

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Approximation methods and heuristics in mathematical programming (90C59)

Related Items (4)

Modified differential evolution with locality induced genetic operators for dynamic optimization ⋮ Differential evolution for dynamic environments with unknown numbers of optima ⋮ An Overview of Multi-population Methods for Dynamic Environments ⋮ Learning Automata for Online Function Evaluation Management in Evolutionary Multi-population Methods for Dynamic Optimization Problems

Cites Work

• Unnamed Item
• Designing evolutionary algorithms for dynamic environments.
• Differential evolution. A practical approach to global optimization. With CD-ROM.
• Mathematical modeling of the thermally stressed state for a solidifying blooming ingot
• Evolutionary swarm cooperative optimization in dynamic environments
• Differential evolution -- a simple and efficient heuristic for global optimization over continuous spaces
• A trigonometric mutation operation to differential evolution
• Empirical analysis of self-adaptive differential evolution
• Bare bones differential evolution
• A numerical study of some modified differential evolution algorithms

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