Spherical search with epsilon constraint and gradient-based repair framework for constrained optimization
In evolutionary computation, search methodologies based on Hyper Cube (HC) are common while those based on Hyper Spherical (HS) methodologies are scarce. Spherical Search (SS), a recently proposed method that is based on HS search methodology has been proven to perform well on bound constraint probl...
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| Vydáno v: | Swarm and evolutionary computation Ročník 82; s. 101370 |
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| Jazyk: | angličtina |
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Elsevier B.V
01.10.2023
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| ISSN: | 2210-6502 |
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| Abstract | In evolutionary computation, search methodologies based on Hyper Cube (HC) are common while those based on Hyper Spherical (HS) methodologies are scarce. Spherical Search (SS), a recently proposed method that is based on HS search methodology has been proven to perform well on bound constraint problems due to its better exploration capability. In this paper, we extend SS to solve Constrained Optimization Problems (COPs) by combining the epsilon constraint handling method with a gradient-based repair framework that comprises of - a) Gradient Repair Method (GRM) which is a combination of Levenberg–Marquardt and Broyden update to reduce the computational complexity and settle numerical instabilities, b) Trigger mechanism that determines when to trigger the GRM, and c) repair ratio that determines the probability of repairing a solution in the population. Ultimately, we verify the performance of the proposed algorithm on IEEE CEC 2017 benchmark COPs along with 11 power system problems from a test suite of real-world COPs. Experimental results show that the proposed algorithm is better than or at least comparable to other advanced algorithms on a wide range of COPs. |
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| AbstractList | In evolutionary computation, search methodologies based on Hyper Cube (HC) are common while those based on Hyper Spherical (HS) methodologies are scarce. Spherical Search (SS), a recently proposed method that is based on HS search methodology has been proven to perform well on bound constraint problems due to its better exploration capability. In this paper, we extend SS to solve Constrained Optimization Problems (COPs) by combining the epsilon constraint handling method with a gradient-based repair framework that comprises of - a) Gradient Repair Method (GRM) which is a combination of Levenberg–Marquardt and Broyden update to reduce the computational complexity and settle numerical instabilities, b) Trigger mechanism that determines when to trigger the GRM, and c) repair ratio that determines the probability of repairing a solution in the population. Ultimately, we verify the performance of the proposed algorithm on IEEE CEC 2017 benchmark COPs along with 11 power system problems from a test suite of real-world COPs. Experimental results show that the proposed algorithm is better than or at least comparable to other advanced algorithms on a wide range of COPs. |
| ArticleNumber | 101370 |
| Author | Yang, Zhuji Mallipeddi, Rammohan Kumar, Abhishek Lee, Dong-Gyu |
| Author_xml | – sequence: 1 givenname: Zhuji surname: Yang fullname: Yang, Zhuji – sequence: 2 givenname: Abhishek surname: Kumar fullname: Kumar, Abhishek – sequence: 3 givenname: Rammohan orcidid: 0000-0001-9071-1145 surname: Mallipeddi fullname: Mallipeddi, Rammohan email: mallipeddi.ram@gmail.com – sequence: 4 givenname: Dong-Gyu orcidid: 0000-0002-1128-7401 surname: Lee fullname: Lee, Dong-Gyu |
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| Cites_doi | 10.1109/TEVC.2007.902851 10.1109/TEVC.2009.2014613 10.1016/j.cad.2010.12.015 10.1090/S0025-5718-1965-0198670-6 10.1109/TEVC.2003.817236 10.1016/j.swevo.2020.100693 10.1162/evco_a_00222 10.1016/j.ins.2021.02.055 10.1109/4235.873238 10.1016/j.asoc.2008.11.003 10.1109/TEVC.2008.927706 10.1109/TEVC.2009.2033582 10.1016/j.asoc.2019.105499 10.1016/j.cor.2005.02.002 10.1109/TEVC.2019.2912204 10.1023/A:1008202821328 10.1080/03052150008941301 10.1016/j.asoc.2019.105734 10.1007/s10898-007-9149-x 10.1109/TSMC.2018.2876335 10.1016/j.advengsoft.2013.12.007 10.1109/4235.585893 10.1109/TEVC.2019.2904900 10.1007/s00521-019-04510-4 |
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| Keywords | Constraint optimization Spherical search ε-constraint Gradient-based repair method |
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