Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/77236
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 |
Appears in Collections: | Conference Paper |
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