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1 – 1 of 1Ali Kaveh and Ataollah Zaerreza
This paper aims to present a new multi-community meta-heuristic optimization algorithm, which is called shuffled shepherd optimization algorithm (SSOA). In this algorithm.
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.
Details