首页|基于混合策略改进的蛇优化算法及其应用

基于混合策略改进的蛇优化算法及其应用

扫码查看
原文链接
  • 国家科技期刊平台
  • NETL
  • NSTL
  • 万方数据
针对基本蛇优化算法求解优化问题时易陷入局部最优的问题，提出了一种基于维度选择策略、选择交配策略和重新分组策略的改进蛇优化算法(SSO)。算法SSO 在基本蛇优化算法在战斗或交配阶段引入维度选择策略，由随机概率选择每条蛇个体在不同维度的位置更新模式，以避免迭代后期出现个体位置停滞现象;同时引入选择交配策略，选择适应度值小的部分个体进行战斗或交配，剩余个体利用探索阶段位置更新公式进行位置更新，以提高战斗或交配阶段的探索能力;采用重新分组策略，个体每迭代10 次都将随机打乱并重新分组，以增加种群多样性，提高算法寻优能力。利用 30 个标准无约束优化问题进行了数值实验，结果表明，相比于基本蛇优化算法 SO 等 6 种对比算法，算法 SSO 的寻优能力更强，且对求解高维优化问题更有效。用算法 SSO 优化 BP 神经网络的初始权值和阈值，实验结果表明所得SSO-BP神经网络在红酒分类和预测鲍鱼年龄时的准确性和稳定性优于其他对比神经网络。
An improved snake optimization algorithm based on hybrid strategies and its application
To solve the problem that the basic snake optimization algorithm easily falls into local op-timization,an improved snake optimization algorithm(SSO)based on dimension selection strategy,se-lection mating strategy,and re-grouping strategy is proposed.The SSO algorithm introduces the dimen-sion selection strategy in the combat or mating stage of the basic snake optimization algorithm.The ran-dom probability is used to select the position update mode of each snake individual in different dimen-sions,so as to avoid the phenomenon of individual position stagnation in the later stage of iteration.The selection mating strategy is introduced in the combat or mating stage,and a part of individuals with smaller fitness values are selected for combat or mating.The remaining individuals use the exploration stage position update formula for position update to improve the exploration ability of the combat or mating stage.The re-grouping strategy is used,and the individuals are randomly disrupted and re-grouped every ten iterations to increase population diversity and improve the optimization ability of the algorithm.Numerical experiments on 30 standard unconstrained optimization problems show that com-pared with six comparative algorithms such as the basic snake optimization algorithm SO,the SSO algo-rithm has stronger optimization ability and is more effective for solving high-dimensional optimization problems.The SSO algorithm is used to optimize the initial weights and thresholds of BP neural net-works.Experimental results show that the SSO-BP neural network has better accuracy and stability than other comparative neural networks in classifying wines and predicting abalone age.

snake optimization algorithmdimension selection strategyselection mating strategyre-grouping strategynumerical experiment

梁昔明、史兰艳、龙文

展开 >

北京建筑大学理学院,北京 102616

贵州财经大学数学与统计学院,贵州 贵阳 550025

蛇优化算法 维度选择策略 选择交配策略 重新分组策略 数值实验

国家自然科学基金贵州省自然科学基金重点项目中央支持地方科研创新团队项目北京建筑大学2021年校级教育科学研究项目

12361106黔科合基础-ZK[2003]重点003PXM2013_014210_000173Y2113

2024

10.3969/j.issn.1007-130X.2024.04.014

计算机工程与科学
国防科学技术大学计算机学院

计算机工程与科学

CSTPCD北大核心
影响因子：0.787
ISSN：1007-130X
年,卷(期)：2024.46(4)
  • 21