基于混合策略的鹈鹕优化算法

doi:10.6040/j.issn.1671-9352.0.2024.024

摘要/Abstract

摘要： 为了提高鹈鹕优化算法的优化性能与稳定性,提出一种基于混合策略的鹈鹕优化算法。在鹈鹕算法备选解的生成机制中使用偏好权重策略,引导备选解进行多样性的探索。采用随机搜索策略更新部分目标函数值较差的备选解位置,使得备选解能够跳出局部最优限制。使用大范围的自适应搜索半径策略,增大各备选解发现更优解的可能。在18个测试函数上结合对比算法开展寻优实验,分析寻优结果并进行Wilcoxon秩和检验,验证了改进后的鹈鹕优化算法具有更好的寻优性能与稳定性。

关键词: 鹈鹕优化算法, 混合策略, 偏好权重, 函数优化

Abstract: In order to improve the optimization performance and stability of the pelican optimization algorithm, a hybrid strategy-based pelican optimization algorithm is proposed. In the generation mechanism of candidate solutions for the pelican algorithm, the preference weight strategy is employed to guide the candidate solutions towards exploring diversity. A random search strategy is used to update partial alternative solution positions, which helps these candidate solutions with poor objective function values escape local optima. A large-range adaptive search radius strategy has been applied to enhance the algorithm, increasing the probability for each candidate solution to discover better solutions. Combined with comparative algorithms, optimization experiments are conducted on 18 test functions. The optimization results are analyzed and Wilcoxon rank sum tests are performed to verify that this improved Pelican optimization algorithm has better optimization performance and stability.

Key words: pelican optimization algorithm, hybrid strategy, preference weight, function optimization

中图分类号:

TP301

刘魏岩,齐迹,梁红,林钰川. 基于混合策略的鹈鹕优化算法[J]. 《山东大学学报(理学版)》, 2025, 60(9): 52-61.

LIU Weiyan, QI Ji, LIANG Hong, LIN Yuchuan. A pelican optimization algorithm based on hybrid strategy[J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2025, 60(9): 52-61.

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