An enhanced seagull optimization algorithm for solving engineering optimization problems

Yanhui Che

doi:10.1007/s10489-021-03155-y

2022-02-21

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Yanhui Che

Dengxu He *

DOI：10.1007/s10489-021-03155-y

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摘要

En 中文

The seagull optimization algorithm (SOA) is a recently proposed meta-heuristic optimization algorithm inspired by seagull foraging behavior. It has the advantages of simple structure and easy implementation. However, it also has some shortcomings, such as easily falling into local optimal and low convergence accuracy when solving complex engineering optimization problems. In this paper, to overcome the defects of the original SOA, an enhanced seagull optimization algorithm (ESOA) based on mutualism mechanism and commensalism mechanism is proposed. To evaluate the performance of the ESOA algorithm, the IEEE CEC2020 benchmark suite is utilized to verify the effectiveness of the ESOA algorithm, and the results are compared and analyzed with the latest meta-heuristic optimization algorithms. In addition, the ESOA algorithm is applied to twelve different types of engineering optimization problems, including pressure vessel design problem, multiple disc clutch brake design problem, three bar truss design problem, car crashworthiness problem, cantilever beam problem, abrasive water jet machine, gas transmission compressor design problem, hydro-static thrust bearing design problem, speed reducer problem, tubular column design problem, I beam design problem and industrial refrigeration system design problem. The convergence curves of ESOA and the comparison results of the latest metaheuristic algorithms are analyzed and compared with those reported in the latest literature. The results show that the ESOA algorithm is an optimization method that can find the optimal solution in engineering design problems, and has strong competitiveness compared with other algorithms.

Keyword:

Seagull optimization algorithm

Mutualism mechanism

Commensalism mechanism

Engineering optimization problems

Metaheuristics