A Weighted Average Algorithm

Version 1.0.2 (11,4 MB) von Jun Cheng
A novel meta-heuristic algorithm named Weighted Average (WAA) is proposed, which is based on the the weighted average position concept.
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Aktualisiert 7. Nov 2024

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In this algorithm, a new metaheuristic optimization algorithm based on the weighted average position concept, and named weighted average algorithm (WAA), is proposed and implemented. In the WAA, the weighted average position for the whole population is first established at each iteration. Subsequently, WAA introduces two movement strategies aimed at achieving a balanced approach between exploitation and exploration capabilities. The determination of movement strategies, whether focused on exploration or exploitation, relies on a parameter function that correlates with random constants and iteration times.
Cheng, Jun, and Wim De Waele. "Weighted average algorithm: a novel meta-heuristic optimization algorithm based on the weighted average position concept." Knowledge-Based Systems (2024): 112564.

Zitieren als

Jun Cheng (2024). A Weighted Average Algorithm (https://www.mathworks.com/matlabcentral/fileexchange/174020-a-weighted-average-algorithm), MATLAB Central File Exchange. Abgerufen.

Cheng, Jun, and Wim De Waele. "Weighted average algorithm: a novel meta-heuristic optimization algorithm based on the weighted average position concept." Knowledge-Based Systems (2024): 112564.

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Erstellt mit R2016b
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1.0.2

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1.0.1

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1.0.0