A Hybrid Method Combining Genetic Algorithm and Hooke-Jeeves Method for Constrained Global Optimization
A new global optimization method combining genetic algorithm and Hooke-Jeeves method to solve a class of constrained optimization problems is studied in this paper. We first introduce the quadratic penalty function method and the exact penalty function method to transform the original constrained op...
| Main Authors: | , |
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| Format: | Journal Article |
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American Institute of Mathematical Sciences
2014
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| Online Access: | http://hdl.handle.net/20.500.11937/46063 |
| _version_ | 1848757456442753024 |
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| author | Long, Q. Wu, Changzhi |
| author_facet | Long, Q. Wu, Changzhi |
| author_sort | Long, Q. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | A new global optimization method combining genetic algorithm and Hooke-Jeeves method to solve a class of constrained optimization problems is studied in this paper. We first introduce the quadratic penalty function method and the exact penalty function method to transform the original constrained optimization problem with general equality and inequality constraints into a sequence of optimization problems only with box constraints. Then, the combination of genetic algorithm and Hooke-Jeeves method is applied to solve the transformed optimization problems. Since Hooke-Jeeves method is good at local search, our proposed method dramatically improves the accuracy and convergence rate of genetic algorithm. In view of the derivative-free of Hooke-Jeeves method, our method only requires information of objective function value which not only can overcome the computational difficulties caused by the ill-condition of the square penalty function, but also can handle the non-differentiability by the exact penalty function. Some well-known test problems are investigated. The numerical results show that our proposed method is efficient and robust. |
| first_indexed | 2025-11-14T09:28:23Z |
| format | Journal Article |
| id | curtin-20.500.11937-46063 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:28:23Z |
| publishDate | 2014 |
| publisher | American Institute of Mathematical Sciences |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-460632023-02-22T06:24:20Z A Hybrid Method Combining Genetic Algorithm and Hooke-Jeeves Method for Constrained Global Optimization Long, Q. Wu, Changzhi constrained global optimization penalty fuction method Hybrid method genetic algorithm Hooke-Jeeves method A new global optimization method combining genetic algorithm and Hooke-Jeeves method to solve a class of constrained optimization problems is studied in this paper. We first introduce the quadratic penalty function method and the exact penalty function method to transform the original constrained optimization problem with general equality and inequality constraints into a sequence of optimization problems only with box constraints. Then, the combination of genetic algorithm and Hooke-Jeeves method is applied to solve the transformed optimization problems. Since Hooke-Jeeves method is good at local search, our proposed method dramatically improves the accuracy and convergence rate of genetic algorithm. In view of the derivative-free of Hooke-Jeeves method, our method only requires information of objective function value which not only can overcome the computational difficulties caused by the ill-condition of the square penalty function, but also can handle the non-differentiability by the exact penalty function. Some well-known test problems are investigated. The numerical results show that our proposed method is efficient and robust. 2014 Journal Article http://hdl.handle.net/20.500.11937/46063 10.3934/jimo.2014.10.1279 American Institute of Mathematical Sciences unknown |
| spellingShingle | constrained global optimization penalty fuction method Hybrid method genetic algorithm Hooke-Jeeves method Long, Q. Wu, Changzhi A Hybrid Method Combining Genetic Algorithm and Hooke-Jeeves Method for Constrained Global Optimization |
| title | A Hybrid Method Combining Genetic Algorithm and Hooke-Jeeves Method for Constrained Global Optimization |
| title_full | A Hybrid Method Combining Genetic Algorithm and Hooke-Jeeves Method for Constrained Global Optimization |
| title_fullStr | A Hybrid Method Combining Genetic Algorithm and Hooke-Jeeves Method for Constrained Global Optimization |
| title_full_unstemmed | A Hybrid Method Combining Genetic Algorithm and Hooke-Jeeves Method for Constrained Global Optimization |
| title_short | A Hybrid Method Combining Genetic Algorithm and Hooke-Jeeves Method for Constrained Global Optimization |
| title_sort | hybrid method combining genetic algorithm and hooke-jeeves method for constrained global optimization |
| topic | constrained global optimization penalty fuction method Hybrid method genetic algorithm Hooke-Jeeves method |
| url | http://hdl.handle.net/20.500.11937/46063 |