ATLA: A novel metaheuristic optimization algorithm inspired by the mating search behavior of longicorn beetles in the nature | Zendy

Xiaokuang Han | Zendy; Xianjun Du | Zendy; Ping Yu | Zendy

Open Access

ATLA: A novel metaheuristic optimization algorithm inspired by the mating search behavior of longicorn beetles in the nature

Author(s) -

Xiaokuang Han,

Xianjun Du,

Ping Yu

Publication year - 2020

Publication title -

iop conference series materials science and engineering

Language(s) - English

Resource type - Journals

eISSN - 1757-899X

pISSN - 1757-8981

DOI - 10.1088/1757-899x/782/5/052028

Subject(s) - metaheuristic , benchmark (surveying) , mating , computer science , mathematical optimization , algorithm , optimization algorithm , process (computing) , local search (optimization) , optimization problem , artificial intelligence , mathematics , biology , ecology , geodesy , geography , operating system

Compared with the traditional optimization algorithms, metaheuristic optimization algorithm has more powerful performance in the optimization problem, which has attracted more and more scholars’ attention. In this paper, a novel metaheuristic optimization algorithm, named artificial transgender longicorn algorithm (ATLA), is proposed, which is inspired by the mating search behavior of longicorn in the nature. ATLA simulates the mechanism of sex pheromone emission and attraction between female and male longicorn beetles, and realizes the process of local search and global search of an optimization problem. Simulation results based on three standard benchmark functions show the good search performance of optimal solution and the effectiveness of the proposed ATLA.

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