An adaptive bio-inspired optimisation model based on the foraging behaviour of a social spider

Cogent Engineering, Vol. 6: 1588681

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Egile Nagusiak: otor, samera, akinyemi, bodunde, aladesanmi, temitope, aderounmu, ganiyu
Formatua: Aldizkaria
Hizkuntza:ingelesa
Argitaratua: cogent OA 2023
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Sarrera elektronikoa:https://ir.oauife.edu.ng/123456789/5615
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author otor, samera
akinyemi, bodunde
aladesanmi, temitope
aderounmu, ganiyu
author_facet otor, samera
akinyemi, bodunde
aladesanmi, temitope
aderounmu, ganiyu
author_sort otor, samera
collection DSpace
description Cogent Engineering, Vol. 6: 1588681
format Journal
id oai:ir.oauife.edu.ng:123456789-5615
institution My University
language English
publishDate 2023
publisher cogent OA
record_format dspace
spelling oai:ir.oauife.edu.ng:123456789-56152023-05-13T18:08:10Z An adaptive bio-inspired optimisation model based on the foraging behaviour of a social spider otor, samera akinyemi, bodunde aladesanmi, temitope aderounmu, ganiyu lgorithms & Complexity; Computing & IT Security; Computer Science; General Keywords: bio-inspired; optimisation; social spider; self-evolving Cogent Engineering, Vol. 6: 1588681 Existing bio-inspired models are challenged with premature convergence among others.In this paper,an adaptive social spider colony optimization model based on the foraging behaviour of social spider was proposed as an optimisation problem. The algorithm mimics the prey capture behaviour of the social spider in which, the spider senses the presence of the prey through vibrations transmitted along the web thread. Spiders are the search agents while the web is the search space of the optimization problem.The natural or biological phenomenon of vibration was modeled using wave theory while optimization theory was considered in optimizing the objective function of the optimisation problem. This objective function was considered to be the frequency of vibration of the spiders and the prey as this is the function that enables the spider differentiates the vibration of the prey from that of neighbouring spider sand therefore forages maximally. To address the parameter tuning problem, the searchpatternwascontrolledbythepositionofthepreyforconvergence.The proposed model was tested for convergence using several benchmark functions with different characteristics to evaluate its performance and results compared to an existing state of the arts’ spider algorithm. Results showed that the proposed model performed better by searching the optimum solution of the benchmark functions used to test the model 2023-05-13T18:02:08Z 2023-05-13T18:02:08Z 2019-11 Journal https://ir.oauife.edu.ng/123456789/5615 en application/pdf cogent OA
spellingShingle lgorithms & Complexity; Computing & IT Security; Computer Science; General Keywords: bio-inspired; optimisation; social spider; self-evolving
otor, samera
akinyemi, bodunde
aladesanmi, temitope
aderounmu, ganiyu
An adaptive bio-inspired optimisation model based on the foraging behaviour of a social spider
title An adaptive bio-inspired optimisation model based on the foraging behaviour of a social spider
title_full An adaptive bio-inspired optimisation model based on the foraging behaviour of a social spider
title_fullStr An adaptive bio-inspired optimisation model based on the foraging behaviour of a social spider
title_full_unstemmed An adaptive bio-inspired optimisation model based on the foraging behaviour of a social spider
title_short An adaptive bio-inspired optimisation model based on the foraging behaviour of a social spider
title_sort adaptive bio inspired optimisation model based on the foraging behaviour of a social spider
topic lgorithms & Complexity; Computing & IT Security; Computer Science; General Keywords: bio-inspired; optimisation; social spider; self-evolving
url https://ir.oauife.edu.ng/123456789/5615
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