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A hybrid simplex search and particle swarm optimization for unconstrained optimization

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  • Fan, Shu-Kai S.
  • Zahara, Erwie

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  • Fan, Shu-Kai S. & Zahara, Erwie, 2007. "A hybrid simplex search and particle swarm optimization for unconstrained optimization," European Journal of Operational Research, Elsevier, vol. 181(2), pages 527-548, September.
    • Handle: RePEc:eee:ejores:v:181:y:2007:i:2:p:527-548
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    1. Russell R. Barton & John S. Ivey, Jr., 1996. "Nelder-Mead Simplex Modifications for Simulation Optimization," Management Science, INFORMS, vol. 42(7), pages 954-973, July.
    2. George E. P. Box, 1957. "Evolutionary Operation: A Method for Increasing Industrial Productivity," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 6(2), pages 81-101, June.
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    1. Xiao, Yi & Liu, John J. & Hu, Yi & Wang, Yingfeng & Lai, Kin Keung & Wang, Shouyang, 2014. "A neuro-fuzzy combination model based on singular spectrum analysis for air transport demand forecasting," Journal of Air Transport Management, Elsevier, vol. 39(C), pages 1-11.
    2. Jianfeng Liu & Nikolaos Ploskas & Nikolaos V. Sahinidis, 2019. "Tuning BARON using derivative-free optimization algorithms," Journal of Global Optimization, Springer, vol. 74(4), pages 611-637, August.
    3. Xu, Meng & Droguett, Enrique López & Lins, Isis Didier & das Chagas Moura, Márcio, 2017. "On the q-Weibull distribution for reliability applications: An adaptive hybrid artificial bee colony algorithm for parameter estimation," Reliability Engineering and System Safety, Elsevier, vol. 158(C), pages 93-105.
    4. Khalid Abdulaziz Alnowibet & Salem Mahdi & Ahmad M. Alshamrani & Karam M. Sallam & Ali Wagdy Mohamed, 2022. "A Family of Hybrid Stochastic Conjugate Gradient Algorithms for Local and Global Minimization Problems," Mathematics, MDPI, vol. 10(19), pages 1-37, October.
    5. Witanowski, Łukasz & Ziółkowski, Paweł & Klonowicz, Piotr & Lampart, Piotr, 2023. "A hybrid approach to optimization of radial inflow turbine with principal component analysis," Energy, Elsevier, vol. 272(C).
    6. Mariani, Viviana Cocco & Coelho, Leandro dos Santos, 2011. "A hybrid shuffled complex evolution approach with pattern search for unconstrained optimization," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(9), pages 1901-1909.
    7. Morteza Ahandani & Mohammad-Taghi Vakil-Baghmisheh & Mohammad Talebi, 2014. "Hybridizing local search algorithms for global optimization," Computational Optimization and Applications, Springer, vol. 59(3), pages 725-748, December.
    8. Weihang Zhu, 2011. "Massively parallel differential evolution—pattern search optimization with graphics hardware acceleration: an investigation on bound constrained optimization problems," Journal of Global Optimization, Springer, vol. 50(3), pages 417-437, July.
    9. Paweł Ziółkowski & Łukasz Witanowski & Stanisław Głuch & Piotr Klonowicz & Michel Feidt & Aimad Koulali, 2024. "Example of Using Particle Swarm Optimization Algorithm with Nelder–Mead Method for Flow Improvement in Axial Last Stage of Gas–Steam Turbine," Energies, MDPI, vol. 17(12), pages 1-29, June.
    10. Waqar Muhammad Ashraf & Ghulam Moeen Uddin & Syed Muhammad Arafat & Sher Afghan & Ahmad Hassan Kamal & Muhammad Asim & Muhammad Haider Khan & Muhammad Waqas Rafique & Uwe Naumann & Sajawal Gul Niazi &, 2020. "Optimization of a 660 MW e Supercritical Power Plant Performance—A Case of Industry 4.0 in the Data-Driven Operational Management Part 1. Thermal Efficiency," Energies, MDPI, vol. 13(21), pages 1-33, October.
    11. Jakubik, Johannes & Binding, Adrian & Feuerriegel, Stefan, 2021. "Directed particle swarm optimization with Gaussian-process-based function forecasting," European Journal of Operational Research, Elsevier, vol. 295(1), pages 157-169.
    12. Shu-Kai S. Fan & Chih-Hung Jen, 2019. "An Enhanced Partial Search to Particle Swarm Optimization for Unconstrained Optimization," Mathematics, MDPI, vol. 7(4), pages 1-16, April.
    13. Liou, Cheng-Dar & Hsieh, Yi-Chih, 2015. "A hybrid algorithm for the multi-stage flow shop group scheduling with sequence-dependent setup and transportation times," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 258-267.
    14. Kuo, R.J. & Lee, Y.H. & Zulvia, Ferani E. & Tien, F.C., 2015. "Solving bi-level linear programming problem through hybrid of immune genetic algorithm and particle swarm optimization algorithm," Applied Mathematics and Computation, Elsevier, vol. 266(C), pages 1013-1026.
    15. Ferreiro, Ana M. & García-Rodríguez, José Antonio & Vázquez, Carlos & e Silva, E. Costa & Correia, A., 2019. "Parallel two-phase methods for global optimization on GPU," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 156(C), pages 67-90.
    16. Maryam Mousavi & Hwa Jen Yap & Siti Nurmaya Musa & Farzad Tahriri & Siti Zawiah Md Dawal, 2017. "Multi-objective AGV scheduling in an FMS using a hybrid of genetic algorithm and particle swarm optimization," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-24, March.

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