What is it about?
This study aimed to improve the search process by developing a bio-inspired optimisation model capable of self-tuning its search pattern to achieve fast convergence while maintaining its balance in exploration and exploitation to avoid premature convergence while searching for an optimal solution.
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Why is it important?
For an algorithm to perform maximally, user-defined parameters require proper tuning. In Bio-Inspired Optimisation models, the values of the parameters of the natural phenomenon used to model them are user-defined, thus leading to the need for the parameters to be tuned for convergence. However, most tunings are done with unpredictable user-defined parameters, which led to premature convergence, exploration and exploitation discrepancies, algorithm complexity and unrealistic results. Consequently, the Bio-Inspired solution search processes are faced with the challenge of parameter tuning for convergence.
Perspectives
This article is well thought of, as it brings about solutions of real-life problems from the natural phenomenon
Bodunde Akinyemi
Obafemi Awolowo University
Read the Original
This page is a summary of: An adaptive bio-inspired optimisation model based on the foraging behaviour of a social spider, Cogent Engineering, March 2019, Taylor & Francis,
DOI: 10.1080/23311916.2019.1588681.
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