Composite Differential Evolution with Modified Oracle Penalty Method for Constrained Optimization Problems
Motivated by recent advancements in differential evolution and constraints handling methods, this paper presents a novel modified oracle penalty function-based composite differential evolution (MOCoDE) for constrained optimization problems (COPs). More specifically, the original oracle penalty funct...
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| Veröffentlicht in: | Mathematical problems in engineering Jg. 2014; H. 2014; S. 1 - 15 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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Cairo, Egypt
Hindawi Publishing Corporation
01.01.2014
John Wiley & Sons, Inc |
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| ISSN: | 1024-123X, 1563-5147 |
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| Abstract | Motivated by recent advancements in differential evolution and constraints handling methods, this paper presents a novel modified oracle penalty function-based composite differential evolution (MOCoDE) for constrained optimization problems (COPs). More specifically, the original oracle penalty function approach is modified so as to satisfy the optimization criterion of COPs; then the modified oracle penalty function is incorporated in composite DE. Furthermore, in order to solve more complex COPs with discrete, integer, or binary variables, a discrete variable handling technique is introduced into MOCoDE to solve complex COPs with mix variables. This method is assessed on eleven constrained optimization benchmark functions and seven well-studied engineering problems in real life. Experimental results demonstrate that MOCoDE achieves competitive performance with respect to some other state-of-the-art approaches in constrained optimization evolutionary algorithms. Moreover, the strengths of the proposed method include few parameters and its ease of implementation, rendering it applicable to real life. Therefore, MOCoDE can be an efficient alternative to solving constrained optimization problems. |
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| AbstractList | Motivated by recent advancements in differential evolution and constraints handling methods, this paper presents a novel modified oracle penalty function-based composite differential evolution (MOCoDE) for constrained optimization problems (COPs). More specifically, the original oracle penalty function approach is modified so as to satisfy the optimization criterion of COPs; then the modified oracle penalty function is incorporated in composite DE. Furthermore, in order to solve more complex COPs with discrete, integer, or binary variables, a discrete variable handling technique is introduced into MOCoDE to solve complex COPs with mix variables. This method is assessed on eleven constrained optimization benchmark functions and seven well-studied engineering problems in real life. Experimental results demonstrate that MOCoDE achieves competitive performance with respect to some other state-of-the-art approaches in constrained optimization evolutionary algorithms. Moreover, the strengths of the proposed method include few parameters and its ease of implementation, rendering it applicable to real life. Therefore, MOCoDE can be an efficient alternative to solving constrained optimization problems. |
| Author | Wang, Ning Jiang, Chuanxian Dong, Minggang Cheng, Xiaohui |
| Author_xml | – sequence: 1 fullname: Jiang, Chuanxian – sequence: 2 fullname: Cheng, Xiaohui – sequence: 3 fullname: Wang, Ning – sequence: 4 fullname: Dong, Minggang |
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| ContentType | Journal Article |
| Copyright | Copyright © 2014 Minggang Dong et al. Copyright © 2014 Minggang Dong et al. Minggang Dong et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
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| SubjectTerms | Competition Complex variables Constraints Evolution Evolutionary algorithms Evolutionary computation Functions (mathematics) Genetic algorithms Handling Mathematical analysis Mathematical problems Objectives Optimization Penalty function Queuing theory Real variables Rendering Science |
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| Title | Composite Differential Evolution with Modified Oracle Penalty Method for Constrained Optimization Problems |
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