Feasibility preserving constraint-handling strategies for real parameter evolutionary optimization
Author
Abstract
Suggested Citation
DOI: 10.1007/s10589-015-9752-6
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Nikhil Padhye & Piyush Bhardawaj & Kalyanmoy Deb, 2013. "Improving differential evolution through a unified approach," Journal of Global Optimization, Springer, vol. 55(4), pages 771-799, April.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Umesh Balande & Deepti Shrimankar, 2019. "SRIFA: Stochastic Ranking with Improved-Firefly-Algorithm for Constrained Optimization Engineering Design Problems," Mathematics, MDPI, vol. 7(3), pages 1-26, March.
- Fernanda Nakano Kazama & Aluizio Fausto Ribeiro Araujo & Paulo Barros Correia & Elaine Guerrero-Peña, 2021. "Constraint-guided evolutionary algorithm for solving the winner determination problem," Journal of Heuristics, Springer, vol. 27(6), pages 1111-1150, December.
- Amir H. Gandomi & Ali R. Kashani, 2018. "Probabilistic evolutionary bound constraint handling for particle swarm optimization," Operational Research, Springer, vol. 18(3), pages 801-823, October.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Feng, Yanling & Li, Guo & Sethi, Suresh P., 2018. "A three-layer chromosome genetic algorithm for multi-cell scheduling with flexible routes and machine sharing," International Journal of Production Economics, Elsevier, vol. 196(C), pages 269-283.
- Thang Trung Nguyen & Nguyen Vu Quynh & Minh Quan Duong & Le Van Dai, 2018. "Modified Differential Evolution Algorithm: A Novel Approach to Optimize the Operation of Hydrothermal Power Systems while Considering the Different Constraints and Valve Point Loading Effects," Energies, MDPI, vol. 11(3), pages 1-30, March.
- Kalyanmoy Deb & Nikhil Padhye, 2014. "Enhancing performance of particle swarm optimization through an algorithmic link with genetic algorithms," Computational Optimization and Applications, Springer, vol. 57(3), pages 761-794, April.
- Yin, Xiuxing & Zhao, Xiaowei & Lin, Jin & Karcanias, Aris, 2020. "Reliability aware multi-objective predictive control for wind farm based on machine learning and heuristic optimizations," Energy, Elsevier, vol. 202(C).
More about this item
Keywords
Constraint-handling; Nonlinear and constrained optimization; Particle swarm optimization; Real-parameter genetic algorithms; Differential evolution;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:coopap:v:62:y:2015:i:3:p:851-890. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.