A Hybrid Search Model for Constrained Optimization
This paper proposes a hybrid model based on decomposition for constrained optimization problems. Firstly, a constrained optimization problem is transformed into a biobjective optimization problem. Then, the biobjective optimization problem is divided into a set of subproblems, and different subprobl...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2022/1190174 |
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| _version_ | 1832568148422819840 |
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| author | Xiaoli Gao Yangfei Yuan Jie Li Weifeng Gao |
| author_facet | Xiaoli Gao Yangfei Yuan Jie Li Weifeng Gao |
| author_sort | Xiaoli Gao |
| collection | DOAJ |
| description | This paper proposes a hybrid model based on decomposition for constrained optimization problems. Firstly, a constrained optimization problem is transformed into a biobjective optimization problem. Then, the biobjective optimization problem is divided into a set of subproblems, and different subproblems are assigned to different Fitness functions by the direction vectors. Different from decomposition-based multiobjective optimization algorithms in which each subproblem is optimized by using the information of its neighboring subproblems, the neighbors of each subproblem are deFined based on corresponding direction vector only in the method. By combining three main components, namely, the local search model, the global search model, and the direction vector adjusting strategy, the population can gradually move toward the global optimal solution. Experiments on two sets of test problems and Five real-world engineering design problems have shown that the proposed method performs better than or is competitive with other compared methods. |
| format | Article |
| id | doaj-art-699f28f0ae6745889cf1db2f271ada84 |
| institution | Kabale University |
| issn | 1607-887X |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-699f28f0ae6745889cf1db2f271ada842025-02-03T00:59:36ZengWileyDiscrete Dynamics in Nature and Society1607-887X2022-01-01202210.1155/2022/1190174A Hybrid Search Model for Constrained OptimizationXiaoli Gao0Yangfei Yuan1Jie Li2Weifeng Gao3Sichuan Jiuzhou Electric Appliance Group Co., Ltd.School of Mathematics and StatisticsSichuan Jiuzhou Electric Appliance Group Co., Ltd.School of Mathematics and StatisticsThis paper proposes a hybrid model based on decomposition for constrained optimization problems. Firstly, a constrained optimization problem is transformed into a biobjective optimization problem. Then, the biobjective optimization problem is divided into a set of subproblems, and different subproblems are assigned to different Fitness functions by the direction vectors. Different from decomposition-based multiobjective optimization algorithms in which each subproblem is optimized by using the information of its neighboring subproblems, the neighbors of each subproblem are deFined based on corresponding direction vector only in the method. By combining three main components, namely, the local search model, the global search model, and the direction vector adjusting strategy, the population can gradually move toward the global optimal solution. Experiments on two sets of test problems and Five real-world engineering design problems have shown that the proposed method performs better than or is competitive with other compared methods.http://dx.doi.org/10.1155/2022/1190174 |
| spellingShingle | Xiaoli Gao Yangfei Yuan Jie Li Weifeng Gao A Hybrid Search Model for Constrained Optimization Discrete Dynamics in Nature and Society |
| title | A Hybrid Search Model for Constrained Optimization |
| title_full | A Hybrid Search Model for Constrained Optimization |
| title_fullStr | A Hybrid Search Model for Constrained Optimization |
| title_full_unstemmed | A Hybrid Search Model for Constrained Optimization |
| title_short | A Hybrid Search Model for Constrained Optimization |
| title_sort | hybrid search model for constrained optimization |
| url | http://dx.doi.org/10.1155/2022/1190174 |
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