Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/77236
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Title: Porcellio scaber algorithm (PSA) for solving constrained optimization problems
Authors: Zhang, Y 
Li, S 
Guo, H
Issue Date: 2017
Source: MATEC Web of Conferences, 2017, v. 139, 33
Abstract: In this paper, we extend a bio-inspired algorithm called the porcellio scaber algorithm (PSA) to solve constrained optimization problems, including a constrained mixed discrete-continuous nonlinear optimization problem. Our extensive experiment results based on benchmark optimization problems show that the PSA has a better performance than many existing methods or algorithms. The results indicate that the PSA is a promising algorithm for constrained optimization.
Publisher: EDP Sciences
Journal: MATEC Web of conferences 
ISSN: 2261-236X
DOI: 10.1051/matecconf/201713900033
Rights: © The Authors, published by EDP Sciences, 2017
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/).
The following publication Zhang, Y., Li, S., & Guo, H. (2017). Porcellio scaber algorithm (PSA) for solving constrained optimization problems. MATEC Web of Conferences, 139, 33 is available at https://doi.org/10.1051/matecconf/201713900033
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