TY - GEN
T1 - Seven Sisters Optimization Algorithm
AU - Saxena, Ayan
AU - Kumar Yadav, Anshul
AU - Kumar, Rajesh
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - This research proposes a new swarm-based meta-heuristic algorithm named Seven Sisters Optimizer (SSO) in-spired by the Jungle Babbler bird flock (commonly known as Seven sisters or Seven Brothers (in Hindi)). Jungle Babbler's calls are structurally and functionally organized to serve as a coherent communication system. They have 15 different types of communication classified as affiliative (friendly), with seven call types, and agonistic (unfriendly), with eight call types. The flock head, the sentinel bird, is tasked with the keep tab on optimal habitat and orients the flock members as affiliative and agonistic. The proposed algorithm is tested on 13 well-known benchmark functions. The results of the proposed SSO are verified by a comparative study of of SSO with nine other existing optimization algorithms, which include the most widely used meta-heuristics, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) as well as Gravitational Search Algorithm (GSA), Flower Polli-nation Algorithm (FPA), Moth-Flame Optimization (MFO), Bat Algorithm (BOA), Firefly Algorithm (FA), Cuckoo Search Algorithm (CS) along with high-performance optimizer LSHADE-SPACMA (LSP). To evaluate the constraint handling capacity of the proposed algorithm ie SSO, it is further tested on a gear design problem, and the results are compared with different classical and swarm-based optimization approaches. The results demonstrate that the proposed SSO exploration and exploitation capabilities are superior as compared to the other optimizers.
AB - This research proposes a new swarm-based meta-heuristic algorithm named Seven Sisters Optimizer (SSO) in-spired by the Jungle Babbler bird flock (commonly known as Seven sisters or Seven Brothers (in Hindi)). Jungle Babbler's calls are structurally and functionally organized to serve as a coherent communication system. They have 15 different types of communication classified as affiliative (friendly), with seven call types, and agonistic (unfriendly), with eight call types. The flock head, the sentinel bird, is tasked with the keep tab on optimal habitat and orients the flock members as affiliative and agonistic. The proposed algorithm is tested on 13 well-known benchmark functions. The results of the proposed SSO are verified by a comparative study of of SSO with nine other existing optimization algorithms, which include the most widely used meta-heuristics, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) as well as Gravitational Search Algorithm (GSA), Flower Polli-nation Algorithm (FPA), Moth-Flame Optimization (MFO), Bat Algorithm (BOA), Firefly Algorithm (FA), Cuckoo Search Algorithm (CS) along with high-performance optimizer LSHADE-SPACMA (LSP). To evaluate the constraint handling capacity of the proposed algorithm ie SSO, it is further tested on a gear design problem, and the results are compared with different classical and swarm-based optimization approaches. The results demonstrate that the proposed SSO exploration and exploitation capabilities are superior as compared to the other optimizers.
KW - algorithm
KW - metaheuristics
KW - optimization
KW - seven sisters
UR - http://www.scopus.com/inward/record.url?scp=85187325734&partnerID=8YFLogxK
U2 - 10.1109/INCOFT60753.2023.10425483
DO - 10.1109/INCOFT60753.2023.10425483
M3 - Conference contribution
AN - SCOPUS:85187325734
T3 - 2023 2nd International Conference on Futuristic Technologies, INCOFT 2023
BT - 2023 2nd International Conference on Futuristic Technologies, INCOFT 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd IEEE International Conference on Futuristic Technologies, INCOFT 2023
Y2 - 24 November 2023 through 26 November 2023
ER -