A Weighted Spider Swarm Intelligent Swarm Optimization Algorithm

JIANG Shuang; LIN Dan

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A Weighted Spider Swarm Intelligent Swarm Optimization Algorithm

更新时间：2026-09-04

- A Weighted Spider Swarm Intelligent Swarm Optimization Algorithm
- Vol. 35, Issue 10, Pages: 1-6(2018)
- 作者机构：
  
  天津大学数学学院,天津,300350
- 作者简介：
- 基金信息：
- DOI：
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- Published：2018
- 稿件说明：
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姜爽, 林丹. 一种增加权重的蜘蛛猴优化算法[J]. 微电子学与计算机, 2018, 35(10): 1-6, 12.

JIANG Shuang, LIN Dan. A Weighted Spider Swarm Intelligent Swarm Optimization Algorithm[J]. 2018, 35(10): 1-6.
姜爽, 林丹. 一种增加权重的蜘蛛猴优化算法[J]. 微电子学与计算机, 2018, 35(10): 1-6, 12. DOI：

JIANG Shuang, LIN Dan. A Weighted Spider Swarm Intelligent Swarm Optimization Algorithm[J]. 2018, 35(10): 1-6. DOI：

摘要

本文提出了增加权重的蜘蛛猴算法(WSMO).为进一步提高蜘蛛猴算法(SMO)的性能

在本地领导者阶段和本地领导者决策阶段对蜘蛛猴个体的原位置引入线性递减的惯性权重

该算法可以在迭代前期增加种群的多样性

在迭代后期增加局部搜索能力.通过六个基准函数的数值实验结果表明改进的算法比原始蜘蛛猴算法在收敛速度、寻优精度和鲁棒性等均有改进

特别是在求解多峰函数优化问题时算法性能的改善更加显著.

Abstract

This paper proposes a weighted spider monkey algorithm (WSMO). In order to further improve the performance of the spider-monkey algorithm (SMO)

a linear decreasing inertia weight is introduced into the spider monkey individuals home position in the local leaders and local leaders decision-making stages. This algorithm can increase the diversity of the population in the early iteration and increase the local search capabilities in the later iteration. The experimental results of six benchmark functions show that the improved algorithm is better than the original spider monkey algorithm in terms of convergence speed

optimization accuracy and robustness

especially in the optimization of multimodal function optimization problems.

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references

Al Azza A A, Al Jodah A A, Harackiewicz F J. Spider monkey optimization: a novel technique for antenna optimization[J]. IEEE Antennas and Wireless Propagation Letters, 2016(15): 1016-1019. DOI: 1016

Agrawal A, Farswan P, Agrawal V, et al. On the hybridization of spider monkey optimization and genetic algorithms[C]// Proceedings of Sixth International Conference on Soft Computing for Problem Solving. Singapore, Springer, 2017: 185-196.

Singh U, Salgotra R. Optimal synthesis of linear antenna arrays using modified spider monkey optimization[J]. Arabian Journal for Science and Engineering, 2016, 41(8): 2957-2973. DOI: 2957

Kumari R, Sharma V K. Fitness based position update in spider monkey optimization algorithm[J]. Procedia Computer Science, 2015(62): 442-449. DOI: 442

杜振鑫, 王兆青.一种改进的动态改变惯性权重的粒子群算法[J].微电子学与计算机, 2011, 28(3):85-88. DOI: 85

Kumar S, Kumari R.Modified position update in spider monkey optimization algorithm [C]//Proceedings of International Journal of Emerging Technologies in Computational and Applied Sciences IJETCAS. [s.l.] 2014.

Bansal J C, Sharma H, Jadon S S, et al.Spider monkey optimization algorithm for numerical optimization[J]. Memetic computing, 2014, 6(1): 31-47. DOI: 31

Sharma A, Panigrahi B K. Ageist spider monkey optimization algorithm [J].Swarm and Evolutionary Computation, 2016(28): 58-77. DOI: 58

Berlin, Heidelberg Gupta K, Deep K. Tournament selection based probability schemein spider monkey optimization algorithm[M].Berlin, Heidelberg:Springer Press, 2016.

Agarwal N, Jain S C. Fast convergent spider mnkey optimization algorithm[C]// Proceedings of Sixth International Conference on Soft Computing for Problem Solving. Springer, Singapore, 2017: 42-51.

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