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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Bibliographic Details
Published in:Arabian journal for science and engineering (2011) 2022, Vol.47 (3), p.3551-3571
Main Authors: Srivastava, Abhishek, Das, Dushmanta Kumar
Format: Article
Language:English
Subjects:
Algorithms
Crime
Emission analysis
Engineering
Heuristic methods
Humanities and Social Sciences
multidisciplinary
Multiple objective analysis
Optimization
Optimization algorithms
Optimization techniques
Performance evaluation
Research Article-Electrical Engineering
Science
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Summary: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.
ISSN:2193-567X
1319-8025
2191-4281
DOI:10.1007/s13369-021-06446-1