改进磷虾群算法及其在结构优化中的应用

Improved krill algorithm and its application in structural optimization

本文针对标准磷虾群算法(KH)存在收敛速度较慢、计算精度不够和对复杂问题易陷入局部最优解的缺陷做出改进与完善,提出一种融合改进差分进化算子和S型自适应惯性权重的改进磷虾群算法(SDEKH)。通过多种标准测试函数对SDEKH、KH等智能算法进行对比测试,验证了SDEKH的优良性能;并运用SDEKH对桁架结构进行优化设计,通过与其他方法的优化结果对比验证了SDEKH的优化效率和精度均有提升,为工程结构优化设计提供了一种更加高效、精准的方法。

In this paper,the standard krill algorithm(KH)has the disadvantages of slow convergence speed,insufficient calculation accuracy and easy to fall into local optimal solution for complex problems,an improved krill algorithm(SDEKH)which combines improved differential evolution operator and S-type adaptive inertia weight is proposed in this paper.Through a variety of standard test functions to compare and test a variety of intelligent algorithms such as SDEKH and KH,the excellent performance of SDEKH is verified,and SDEKH is used to optimize the truss structure,and the optimization results of SDEKH are compared with other methods to verify that the optimization efficiency and accuracy are improved,which provides a more efficient and accurate method for engineering structure optimization design.