Whale Swarm Algorithm for Function Optimization

نویسندگان

  • Bing Zeng
  • Liang Gao
  • Xinyu Li
چکیده

Increasing nature-inspired metaheuristic algorithms are applied to solving the real-world optimization problems, as they have some advantages over the classical methods of numerical optimization. This paper has proposed a new nature-inspired metaheuristic called Whale Swarm Algorithm for function optimization, which is inspired by the whales’ behavior of communicating with each other via ultrasound for hunting. The proposed Whale Swarm Algorithm has been compared with several popular metaheuristic algorithms on comprehensive performance metrics. According to the experimental results, Whale Swarm Algorithm has a quite competitive performance when compared with other algorithms. Keywords—whale Swarm Algorithm; ultrasound; natureinspired; metaheuristic; real-world optimization problems; function optimization.

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تاریخ انتشار 2017