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PSSA: Polar Coordinate Salp Swarm Algorithm for Curve Design Problems

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Abstract

This paper proposes a modified optimization algorithm called polar coordinate salp swarm algorithm (PSSA). The main inspiration of PSSA is the aggregation chain and foraging trajectory of salp is spiral. Some curves are extremely complex when represented in Cartesian coordinate system, but if they are expressed in polar coordinates, it becomes very simple and easy to handle, and polar coordinates are widely used in scientific computing and engineering issues. It will be more intuitive and convenient if use polar coordinates to define the foraging and aggregation process of salps. At the same time, different from other algorithms proposed in the past, the PSSA directly initialize individuals in polar space instead of using mapping functions to convert to polar coordinates, change the position of particles by updating polar angles and polar diameters. This algorithm is tested on two complex polar coordinate equations, several curve approximation problems and engineering design problems using PSSA. The experimental results illustrated that the proposed PSSA algorithm is superior to the state-of-the-art metaheuristic algorithms in terms of the performance measures.

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Acknowledgements

This work is supported by National Science Foundation of China under Grant No. 61563008, and by Project of Guangxi Natural Science Foundation under Grant No. 2018GXNSFAA138146.

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Authors and Affiliations

  1. College of Information Science and Engineering, Guangxi University for Nationalities, Nanning, 530006, China

    Zhehong Xiang, Yongquan Zhou, Qifang Luo & Chunming Wen

  2. Key Laboratory of Guangxi High Schools Complex System and Computational Intelligence, Nanning, 530006, China

    Yongquan Zhou & Qifang Luo

  3. Guangxi Key Laboratories of Hybrid Computation and IC Design Analysis, Nanning, 530006, China

    Yongquan Zhou

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  1. Zhehong Xiang
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Correspondence to Yongquan Zhou.

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Xiang, Z., Zhou, Y., Luo, Q. et al. PSSA: Polar Coordinate Salp Swarm Algorithm for Curve Design Problems. Neural Process Lett 52, 615–645 (2020). https://doi.org/10.1007/s11063-020-10271-2

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