A vector-encirclement-model-based sparrow search algorithm for engineering optimization and numerical optimization problems

Jiale Hong

doi:10.1016/j.asoc.2022.109777

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A vector-encirclement-model-based sparrow search algorithm for engineering optimization and numerical optimization problems

2022-12-01

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DOI：10.1016/j.asoc.2022.109777

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Abstract

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Sparrow search algorithm (SSA) is a new global optimization tool with high performance. In order to further improve its global and local search abilities, in this paper, an improved SSA (ISSA) is put forward where the main novelties lie in the producer centralization strategy, the vector encirclement model and the direction selection strategy. The producer centralization strategy is designed to update the position of producer with the hope of improving the global search ability of the producer, while the vector encirclement model and the direction selection strategy are proposed to update the position of scrounger for the purpose of improving the local search ability of scrounger. For the comparison purpose, the performances of the proposed ISSA and the existing excellent algorithms are tested in CEC2017 benchmark functions and 30 real-world constrained optimization problems. The experimental results demonstrate that the proposed ISSA substantially improves the convergence rate, optimization accuracy, stability of the SSA and can solve a wide range of real-world constrained optimization problems successfully with satisfactory performances. Finally, the proposed ISSA is successfully applied in the trajectory optimization of mechanical arms.(c) 2022 Elsevier B.V. All rights reserved.

Keywords:

Engineering optimization problems

Numerical optimization problems

Sparrow search algorithm

Trajectory optimization

Vector encirclement model