Multiobjective Optimization Method Based on Adaptive Parameter Harmony Search Algorithm
The present trend in industries is to improve the techniques currently used in design and manufacture of products in order to meet the challenges of the competitive market. The crucial task nowadays is to find the optimal design and machining parameters so as to minimize the production costs. Design...
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2015/165601 |
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| author | P. Sabarinath M. R. Thansekhar R. Saravanan |
| author_facet | P. Sabarinath M. R. Thansekhar R. Saravanan |
| author_sort | P. Sabarinath |
| collection | DOAJ |
| description | The present trend in industries is to improve the techniques currently used in design and manufacture of products in order to meet the challenges of the competitive market. The crucial task nowadays is to find the optimal design and machining parameters so as to minimize the production costs. Design optimization involves more numbers of design variables with multiple and conflicting objectives, subjected to complex nonlinear constraints. The complexity of optimal design of machine elements creates the requirement for increasingly effective algorithms. Solving a nonlinear multiobjective optimization problem requires significant computing effort. From the literature it is evident that metaheuristic algorithms are performing better in dealing with multiobjective optimization. In this paper, we extend the recently developed parameter adaptive harmony search algorithm to solve multiobjective design optimization problems using the weighted sum approach. To determine the best weightage set for this analysis, a performance index based on least average error is used to determine the index of each weightage set. The proposed approach is applied to solve a biobjective design optimization of disc brake problem and a newly formulated biobjective design optimization of helical spring problem. The results reveal that the proposed approach is performing better than other algorithms. |
| format | Article |
| id | doaj-art-f28a56e3e6d2473fb345ea94bd66dd86 |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-f28a56e3e6d2473fb345ea94bd66dd862025-02-03T06:06:35ZengWileyJournal of Applied Mathematics1110-757X1687-00422015-01-01201510.1155/2015/165601165601Multiobjective Optimization Method Based on Adaptive Parameter Harmony Search AlgorithmP. Sabarinath0M. R. Thansekhar1R. Saravanan2K.L.N College of Engineering, Pottapalayam 630611, IndiaK.L.N College of Engineering, Pottapalayam 630611, IndiaSri Krishna College of Technology, Coimbatore 641 042, IndiaThe present trend in industries is to improve the techniques currently used in design and manufacture of products in order to meet the challenges of the competitive market. The crucial task nowadays is to find the optimal design and machining parameters so as to minimize the production costs. Design optimization involves more numbers of design variables with multiple and conflicting objectives, subjected to complex nonlinear constraints. The complexity of optimal design of machine elements creates the requirement for increasingly effective algorithms. Solving a nonlinear multiobjective optimization problem requires significant computing effort. From the literature it is evident that metaheuristic algorithms are performing better in dealing with multiobjective optimization. In this paper, we extend the recently developed parameter adaptive harmony search algorithm to solve multiobjective design optimization problems using the weighted sum approach. To determine the best weightage set for this analysis, a performance index based on least average error is used to determine the index of each weightage set. The proposed approach is applied to solve a biobjective design optimization of disc brake problem and a newly formulated biobjective design optimization of helical spring problem. The results reveal that the proposed approach is performing better than other algorithms.http://dx.doi.org/10.1155/2015/165601 |
| spellingShingle | P. Sabarinath M. R. Thansekhar R. Saravanan Multiobjective Optimization Method Based on Adaptive Parameter Harmony Search Algorithm Journal of Applied Mathematics |
| title | Multiobjective Optimization Method Based on Adaptive Parameter Harmony Search Algorithm |
| title_full | Multiobjective Optimization Method Based on Adaptive Parameter Harmony Search Algorithm |
| title_fullStr | Multiobjective Optimization Method Based on Adaptive Parameter Harmony Search Algorithm |
| title_full_unstemmed | Multiobjective Optimization Method Based on Adaptive Parameter Harmony Search Algorithm |
| title_short | Multiobjective Optimization Method Based on Adaptive Parameter Harmony Search Algorithm |
| title_sort | multiobjective optimization method based on adaptive parameter harmony search algorithm |
| url | http://dx.doi.org/10.1155/2015/165601 |
| work_keys_str_mv | AT psabarinath multiobjectiveoptimizationmethodbasedonadaptiveparameterharmonysearchalgorithm AT mrthansekhar multiobjectiveoptimizationmethodbasedonadaptiveparameterharmonysearchalgorithm AT rsaravanan multiobjectiveoptimizationmethodbasedonadaptiveparameterharmonysearchalgorithm |