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.
引用
Jun Cheng (2026). A Weighted Average Algorithm (https://jp.mathworks.com/matlabcentral/fileexchange/174020-a-weighted-average-algorithm), MATLAB Central File Exchange. 取得日: .
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.
MATLAB リリースの互換性
作成:
R2016b
すべてのリリースと互換性あり
