Criminal Search Optimization Algorithm: A Population-Based Meta-Heuristic Optimization Technique to Solve Real-World Optimization Problems
Optimization techniques are widely used to solve variety of problems related to the fields of engineering, statistics, finance, etc. In this article, a new optimization algorithm named criminal search optimization algorithm (CSOA) has been proposed. This proposed algorithm is inspired by policemen a...
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| Published in | Arabian journal for science and engineering (2011) Vol. 47; no. 3; pp. 3551 - 3571 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.03.2022
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2193-567X 1319-8025 2191-4281 |
| DOI | 10.1007/s13369-021-06446-1 |
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| Abstract | Optimization techniques are widely used to solve variety of problems related to the fields of engineering, statistics, finance, etc. In this article, a new optimization algorithm named criminal search optimization algorithm (CSOA) has been proposed. This proposed algorithm is inspired by policemen and replicates the strategies and intelligence used by a team of the policemen to catch a criminal for a crime. The performance of CSOA is validated using two suites of benchmark functions (CEC-2005 and CEC-2020). Further, the proposed method is used to solve a multi-objective real-world optimization problem, i.e. a combined emission economic dispatch problem. To evaluate the performance of the proposed method, five test cases have been considered in this study. The results obtained are compared with other existing well-known optimization methods to show the superiority of the proposed CSOA method. |
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| AbstractList | Optimization techniques are widely used to solve variety of problems related to the fields of engineering, statistics, finance, etc. In this article, a new optimization algorithm named criminal search optimization algorithm (CSOA) has been proposed. This proposed algorithm is inspired by policemen and replicates the strategies and intelligence used by a team of the policemen to catch a criminal for a crime. The performance of CSOA is validated using two suites of benchmark functions (CEC-2005 and CEC-2020). Further, the proposed method is used to solve a multi-objective real-world optimization problem, i.e. a combined emission economic dispatch problem. To evaluate the performance of the proposed method, five test cases have been considered in this study. The results obtained are compared with other existing well-known optimization methods to show the superiority of the proposed CSOA method. |
| Author | Das, Dushmanta Kumar Srivastava, Abhishek |
| Author_xml | – sequence: 1 givenname: Abhishek surname: Srivastava fullname: Srivastava, Abhishek organization: Department of Electrical and Electronics Engineering, National Institute of Technology Nagaland – sequence: 2 givenname: Dushmanta Kumar surname: Das fullname: Das, Dushmanta Kumar organization: Department of Electrical and Electronics Engineering, National Institute of Technology Nagaland |
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| Keywords | CEC-2005 benchmark functions CEC-2020 benchmark functions Combined emission and economic dispatch (CEED) problem Meta-heuristic techniques |
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| Title | Criminal Search Optimization Algorithm: A Population-Based Meta-Heuristic Optimization Technique to Solve Real-World Optimization Problems |
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