Multi-objective optimization in the presence of practical constraints using non-dominated sorting hybrid cuckoo search algorithm
A novel optimization algorithm is proposed to solve single and multi-objective optimization problems with generation fuel cost, emission, and total power losses as objectives. The proposed method is a hybridization of the conventional cuckoo search algorithm and arithmetic crossover operations. Thus...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2015-12-01
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| Series: | Engineering Science and Technology, an International Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S221509861500049X |
| _version_ | 1819261626584399872 |
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| author | M. Balasubbareddy S. Sivanagaraju Chintalapudi V. Suresh |
| author_facet | M. Balasubbareddy S. Sivanagaraju Chintalapudi V. Suresh |
| author_sort | M. Balasubbareddy |
| collection | DOAJ |
| description | A novel optimization algorithm is proposed to solve single and multi-objective optimization problems with generation fuel cost, emission, and total power losses as objectives. The proposed method is a hybridization of the conventional cuckoo search algorithm and arithmetic crossover operations. Thus, the non-linear, non-convex objective function can be solved under practical constraints. The effectiveness of the proposed algorithm is analyzed for various cases to illustrate the effect of practical constraints on the objectives' optimization. Two and three objective multi-objective optimization problems are formulated and solved using the proposed non-dominated sorting-based hybrid cuckoo search algorithm. The effectiveness of the proposed method in confining the Pareto front solutions in the solution region is analyzed. The results for single and multi-objective optimization problems are physically interpreted on standard test functions as well as the IEEE-30 bus test system with supporting numerical and graphical results and also validated against existing methods. |
| first_indexed | 2024-12-23T19:44:48Z |
| format | Article |
| id | doaj.art-173920fe877e406592ed35012b761859 |
| institution | Directory Open Access Journal |
| issn | 2215-0986 |
| language | English |
| last_indexed | 2024-12-23T19:44:48Z |
| publishDate | 2015-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Engineering Science and Technology, an International Journal |
| spelling | doaj.art-173920fe877e406592ed35012b7618592022-12-21T17:33:33ZengElsevierEngineering Science and Technology, an International Journal2215-09862015-12-0118460361510.1016/j.jestch.2015.04.005Multi-objective optimization in the presence of practical constraints using non-dominated sorting hybrid cuckoo search algorithmM. Balasubbareddy0S. Sivanagaraju1Chintalapudi V. Suresh2Department of Electrical and Electronics Engineering, Prakasam Engineering College, Kandukur, Andhra Pradesh 523105, IndiaDepartment of Electrical and Electronics Engineering, University College of Engineering, JNTUK, Kakinada, Andhra Pradesh, IndiaResearch Scholar, Department of Electrical and Electronics Engineering, University College of Engineering, JNTUK, Kakinada, Andhra Pradesh, IndiaA novel optimization algorithm is proposed to solve single and multi-objective optimization problems with generation fuel cost, emission, and total power losses as objectives. The proposed method is a hybridization of the conventional cuckoo search algorithm and arithmetic crossover operations. Thus, the non-linear, non-convex objective function can be solved under practical constraints. The effectiveness of the proposed algorithm is analyzed for various cases to illustrate the effect of practical constraints on the objectives' optimization. Two and three objective multi-objective optimization problems are formulated and solved using the proposed non-dominated sorting-based hybrid cuckoo search algorithm. The effectiveness of the proposed method in confining the Pareto front solutions in the solution region is analyzed. The results for single and multi-objective optimization problems are physically interpreted on standard test functions as well as the IEEE-30 bus test system with supporting numerical and graphical results and also validated against existing methods.http://www.sciencedirect.com/science/article/pii/S221509861500049XHybrid cuckoo search algorithmNon-dominated sortingMulti-objective optimizationGeneration fuel costEmissionTotal power lossPractical constraints |
| spellingShingle | M. Balasubbareddy S. Sivanagaraju Chintalapudi V. Suresh Multi-objective optimization in the presence of practical constraints using non-dominated sorting hybrid cuckoo search algorithm Engineering Science and Technology, an International Journal Hybrid cuckoo search algorithm Non-dominated sorting Multi-objective optimization Generation fuel cost Emission Total power loss Practical constraints |
| title | Multi-objective optimization in the presence of practical constraints using non-dominated sorting hybrid cuckoo search algorithm |
| title_full | Multi-objective optimization in the presence of practical constraints using non-dominated sorting hybrid cuckoo search algorithm |
| title_fullStr | Multi-objective optimization in the presence of practical constraints using non-dominated sorting hybrid cuckoo search algorithm |
| title_full_unstemmed | Multi-objective optimization in the presence of practical constraints using non-dominated sorting hybrid cuckoo search algorithm |
| title_short | Multi-objective optimization in the presence of practical constraints using non-dominated sorting hybrid cuckoo search algorithm |
| title_sort | multi objective optimization in the presence of practical constraints using non dominated sorting hybrid cuckoo search algorithm |
| topic | Hybrid cuckoo search algorithm Non-dominated sorting Multi-objective optimization Generation fuel cost Emission Total power loss Practical constraints |
| url | http://www.sciencedirect.com/science/article/pii/S221509861500049X |
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