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Salp swarm algorithm simulates the behaviour of salps in the salp chain during navigating and foraging in oceans. Salp swarm optimizer is inspired by salps and recently proposed metaheuristics search algorithm is based on ocean Salps. The salps form a chain (salp chain) for achieving precise locomotion by using coordinate changes. In the proposed research, a hybrid variant of salp swarm algorithm has been developed using a simulated annealing algorithm and named as SSA-SA. The proposed algorithm has been tested for various unimodal, multimodal and fixed-dimensions problems and corresponding…mehr

Produktbeschreibung
Salp swarm algorithm simulates the behaviour of salps in the salp chain during navigating and foraging in oceans. Salp swarm optimizer is inspired by salps and recently proposed metaheuristics search algorithm is based on ocean Salps. The salps form a chain (salp chain) for achieving precise locomotion by using coordinate changes. In the proposed research, a hybrid variant of salp swarm algorithm has been developed using a simulated annealing algorithm and named as SSA-SA. The proposed algorithm has been tested for various unimodal, multimodal and fixed-dimensions problems and corresponding results are compared with classical salp swarm optimizer. Experimentally, it has been observed that the proposed hybrid optimizer perform much better than other recently proposed algorithms and has been applied to solve power system optimization problems including multi-objective scheduling and dispatch problem of the realistic power system.
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Autorenporträt
Dr. Vikram Kumar  - Associate Professor (Domain: Power Systems).School of Electronics and Electrical EngineeringLovely Professional University, Phagwara