1. Shuffled shepherd optimization method: a new Meta-heuristic algorithm.
- Author
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Kaveh, Ali and Zaerreza, Ataollah
- Subjects
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MATHEMATICAL optimization , *BENCHMARK problems (Computer science) , *HEURISTIC algorithms , *HEURISTIC programming , *METAHEURISTIC algorithms , *ALGORITHMS - Abstract
Purpose: This paper aims to present a new multi-community meta-heuristic optimization algorithm, which is called shuffled shepherd optimization algorithm (SSOA). In this algorithm. Design/methodology/approach: The agents are first separated into multi-communities and the optimization process is then performed mimicking the behavior of a shepherd in nature operating on each community. Findings: A new multi-community meta-heuristic optimization algorithm called a shuffled shepherd optimization algorithm is developed in this paper and applied to some attractive examples. Originality/value: A new metaheuristic is presented and tested with some classic benchmark problems and some attractive structures are optimized. [ABSTRACT FROM AUTHOR]
- Published
- 2020
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