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Sci Rep

Title:		An improved spider optimization algorithm coordinated by pheromones
Author(s):		Feng S; Hu Y; Chen Y; Huang M;
Address:		"School of Information and Communication Engineering, Hainan University, No. 58 Renmin Avenue, Haikou, 570028, Hainan, China. School of Science, Hainan University, No. 58 Renmin Avenue, Haikou, 570028, Hainan, China. School of Information and Communication Engineering, Hainan University, No. 58 Renmin Avenue, Haikou, 570028, Hainan, China. huangmx09@hainanu.edu.cn. State Key Laboratory of Marine Resource Utilization in the South China Sea, Hainan University, No. 58 Renmin Avenue, Haikou, 570028, Hainan, China. huangmx09@hainanu.edu.cn"
Journal Title:		Sci Rep
Year:		2022
Volume:		20220408
Issue:		1
Page Number:		5962 -
DOI:		10.1038/s41598-022-09800-x
ISSN/ISBN:		2045-2322 (Electronic) 2045-2322 (Linking)
Abstract:		"Swarm intelligence algorithm is an important evolutionary computation method that optimizes the objective function by imitating the behaviors of various organisms in nature. A two-stage swarm intelligence algorithm named spider pheromone coordination algorithm (SPC) is proposed in this paper. SPC tries to explore as many feasible solutions as possible on the cobweb at the positioning stage. It simulates the release and reception of different pheromones between spiders at the hunting stage, and then spiders move towards prey under the co-action of winds and pheromones. Different from the existing algorithms, SPC simulates the process that spiders accomplish intra-species communications through different pheromones and considers the impact on spider wind movement. A large number of typical benchmark functions are used in comparative numerical experiments to verify the performances of SPC. Experiments are made to compare SPC with a series of swarm intelligence algorithms, showing that SPC has higher convergence accuracy and stronger global searchability, effectively keeping the diversity of feasible solutions"
Keywords:		Algorithms Animals Benchmarking *Pheromones *Spiders;
Notes:		"MedlineFeng, Siling Hu, Yue Chen, Yinjie Huang, Mengxing eng Research Support, Non-U.S. Gov't England 2022/04/10 Sci Rep. 2022 Apr 8; 12(1):5962. doi: 10.1038/s41598-022-09800-x"