摘要
为了解决具有约束的非线性优化问题,本文将增广拉格朗日乘子法和鱼群算法相结合用于非线性问题的全局优化,即用人工鱼群算法寻找增广拉格朗日函数的近似最优解,并将该近似解用于拉格朗日乘子和惩罚因子等参数的更新.同时,简要分析了人工鱼群算法的随机收敛性.仿真结果证明,与自适应惩罚遗传算法相比,该混合算法在解决约束优化问题中具有优越性和有效性.
A hybrid algorithm which combines the augmented Lagrangian multiplier method with the fish swarm algorithm is presented to solve the problem of constrained nonlinear optimization.The method approximately solves the optimal solution of the augmented Lagrangian function with the fish swarm algorithm,and the solution is applied to update the Lagrangian multipliers and penalty parameters.Stochastic convergence of the artificial fish swarm is analyzed.Compared with an adaptive penalty method for genetic algorithms,simulation results verify the superiority and validity of the proposed hybrid algorithm.
出处
《哈尔滨工业大学学报》
EI
CAS
CSCD
北大核心
2014年第9期55-60,共6页
Journal of Harbin Institute of Technology
基金
国家重点基础研究发展规划资助项目(20126131890302)
航空科学基金资助项目(20125853035)
关键词
增广拉格朗日乘子法
增广拉格朗日函数
鱼群算法
随机收敛性
augmented Lagrangian multiplier method
augmented Lagrangian function
fish swarm algorithm
stochastic convergence
