TY  - JOUR
AB  - 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.
VL  - 37
IS  - 7
SN  - 0264-4401
DO  - 10.1108/EC-10-2019-0481
UR  - https://doi.org/10.1108/EC-10-2019-0481
AU  - Kaveh Ali
AU  - Zaerreza Ataollah
PY  - 2020
Y1  - 2020/01/01
TI  - Shuffled shepherd optimization method: a new Meta-heuristic algorithm
T2  - Engineering Computations
PB  - Emerald Publishing Limited
SP  - 2357
EP  - 2389
Y2  - 2024/04/23
ER  -