Flowchart of improved FOX optimization algorithm.

<div><p>Optimization algorithms are essential for solving many real-world problems. However, challenges such as getting trapped in local minima and effectively balancing exploration and exploitation often limit their performance. This paper introduces an improved variation of the FOX opt...

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Bibliographic Details
Main Author:	Mahmood A. Jumaah (22272371) (author)
Other Authors:	Yossra H. Ali (22272374) (author), Tarik A. Rashid (6519329) (author)
Published:	2025
Subjects:	Neuroscience Ecology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified removing four parameters experimental results showed dynamically scaled step art optimization algorithms solving many real parametric statistical tests effectively balancing exploration achieved 880 wins overall performance metrics fox optimization algorithm exploitation often limit ifox ), incorporating ten real rank tests ifox achieved cec ), balance exploration wilcoxon signed size parameter significant potential primary equations paper introduces original fox local minima involved functions improved variation getting trapped fitness value findings highlight exploitation based evolutionary computation average rank 348 losses 228 ties
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Flowchart of improved FOX optimization algorithm.

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