A robust simulation optimization algorithm using kriging and particle swarm optimization: Application to surgery room optimization

DOI10.1080/03610918.2019.1593452zbMath1497.62351OpenAlexW2937050778WikidataQ128036359 ScholiaQ128036359MaRDI QIDQ5082674

Farshad Seifi, Mohammad Javad Azizi, Samira Moghadam

Publication date: 21 June 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2019.1593452

zbMATH Keywords

kriginghealth carerobust optimizationparticle swarm optimizationmetamodel-based simulation optimization

Mathematics Subject Classification ID

Applications of statistics in engineering and industry; control charts (62P30) Robustness in mathematical programming (90C17)

Uses Software

• ooDACE

Cites Work

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• Handbook of simulation optimization
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• Design and analysis of computer experiments. With comments and a rejoinder by the authors
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• Model-robust designs in multiresponse situations.
• Worst-case global optimization of black-box functions through Kriging and relaxation
• Robust Optimization in Simulation: Taguchi and Krige Combined
• Stochastic Kriging for Simulation Metamodeling
• The Price of Robustness
• Performance Measures Independent of Adjustment: An Explanation and Extension of Taguchi's Signal-to-Noise Ratios
• An integrated joint optimization procedure for robust and tolerance design

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