A hybrid genetic algorithm--neural network strategy for simulation optimization

DOI10.1016/J.AMC.2005.01.024zbMath1103.90410OpenAlexW1964731025MaRDI QIDQ2573594

Ling Wang

Publication date: 22 November 2005

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2005.01.024

zbMATH Keywords

Genetic algorithmNeural networkSimulation optimizationHybrid strategy

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Learning and adaptive systems in artificial intelligence (68T05) Approximation methods and heuristics in mathematical programming (90C59)

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Approximating the objective function's gradient using perceptrons for constrained minimization with application in drag reduction ⋮ Multi-population interactive coevolutionary algorithm for flexible job shop scheduling problems ⋮ Some Monotonicity Results for Stochastic Kriging Metamodels in Sequential Settings ⋮ Hybrid evolutionary optimization of the operation of pipeless plants

Cites Work

• Unnamed Item
• Evolutionary algorithms in noisy environments: theoretical issues and guidelines for practise.
• Optimization via simulation: A review
• Simulation-based optimization using computational intelligence

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