Chaotic Evolutionary Programming for an Engineering Optimization Problem
The aim of the current paper is to present a mimetic algorithm called the chaotic evolutionary programming Powell’s pattern search (CEPPS) algorithm for the solution of the multi-fuel economic load dispatch problem. In the CEPPS algorithm, the exploration process is maintained by chaotic evolutionar...
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MDPI AG
2021-03-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/6/2717 |
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| author | Nirbhow Jap Singh Shakti Singh Vikram Chopra Mohd Asim Aftab S. M. Suhail Hussain Taha Selim Ustun |
| author_facet | Nirbhow Jap Singh Shakti Singh Vikram Chopra Mohd Asim Aftab S. M. Suhail Hussain Taha Selim Ustun |
| author_sort | Nirbhow Jap Singh |
| collection | DOAJ |
| description | The aim of the current paper is to present a mimetic algorithm called the chaotic evolutionary programming Powell’s pattern search (CEPPS) algorithm for the solution of the multi-fuel economic load dispatch problem. In the CEPPS algorithm, the exploration process is maintained by chaotic evolutionary programming, whereas exploitation is taken care off by a pattern search. The proposed CEPPS has two variants based on the Gauss map and the tent map. Seven generalized benchmark test functions and six cases of the multi-fuel economic load dispatch problem are considered for the performance analysis. It is observed from the analysis that the CEPPS solution procedure based on the tent map exhibits superiority to obtain an excellent solution and better convergence characteristics than traditional chaotic evolutionary programming. Further, the performance investigation for the considered economic load dispatch shows that the Gauss map CEPPS solution procedure performs better than the tent map based CEPPS to obtain the solution of the multi-fuel economic dispatch problem. |
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| format | Article |
| id | doaj.art-af0fabf750764fceb65d7b6056da60b1 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T13:08:02Z |
| publishDate | 2021-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-af0fabf750764fceb65d7b6056da60b12023-11-21T10:58:34ZengMDPI AGApplied Sciences2076-34172021-03-01116271710.3390/app11062717Chaotic Evolutionary Programming for an Engineering Optimization ProblemNirbhow Jap Singh0Shakti Singh1Vikram Chopra2Mohd Asim Aftab3S. M. Suhail Hussain4Taha Selim Ustun5Electrical and Instrumentation Engineering Department, Thapar Institute of Engineering and Technology, Patiala 147001, IndiaElectrical and Instrumentation Engineering Department, Thapar Institute of Engineering and Technology, Patiala 147001, IndiaElectrical and Instrumentation Engineering Department, Thapar Institute of Engineering and Technology, Patiala 147001, IndiaElectrical and Instrumentation Engineering Department, Thapar Institute of Engineering and Technology, Patiala 147001, IndiaFukushima Renewable Energy Institute, AIST (FREA), National Institute of Advanced Industrial Science and Technology (AIST), Koriyama 963-0298, JapanFukushima Renewable Energy Institute, AIST (FREA), National Institute of Advanced Industrial Science and Technology (AIST), Koriyama 963-0298, JapanThe aim of the current paper is to present a mimetic algorithm called the chaotic evolutionary programming Powell’s pattern search (CEPPS) algorithm for the solution of the multi-fuel economic load dispatch problem. In the CEPPS algorithm, the exploration process is maintained by chaotic evolutionary programming, whereas exploitation is taken care off by a pattern search. The proposed CEPPS has two variants based on the Gauss map and the tent map. Seven generalized benchmark test functions and six cases of the multi-fuel economic load dispatch problem are considered for the performance analysis. It is observed from the analysis that the CEPPS solution procedure based on the tent map exhibits superiority to obtain an excellent solution and better convergence characteristics than traditional chaotic evolutionary programming. Further, the performance investigation for the considered economic load dispatch shows that the Gauss map CEPPS solution procedure performs better than the tent map based CEPPS to obtain the solution of the multi-fuel economic dispatch problem.https://www.mdpi.com/2076-3417/11/6/2717chaotic evolutionary programmingGauss mapPowell’s pattern searchrobustness testtent map |
| spellingShingle | Nirbhow Jap Singh Shakti Singh Vikram Chopra Mohd Asim Aftab S. M. Suhail Hussain Taha Selim Ustun Chaotic Evolutionary Programming for an Engineering Optimization Problem Applied Sciences chaotic evolutionary programming Gauss map Powell’s pattern search robustness test tent map |
| title | Chaotic Evolutionary Programming for an Engineering Optimization Problem |
| title_full | Chaotic Evolutionary Programming for an Engineering Optimization Problem |
| title_fullStr | Chaotic Evolutionary Programming for an Engineering Optimization Problem |
| title_full_unstemmed | Chaotic Evolutionary Programming for an Engineering Optimization Problem |
| title_short | Chaotic Evolutionary Programming for an Engineering Optimization Problem |
| title_sort | chaotic evolutionary programming for an engineering optimization problem |
| topic | chaotic evolutionary programming Gauss map Powell’s pattern search robustness test tent map |
| url | https://www.mdpi.com/2076-3417/11/6/2717 |
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