This article proposes an exponential adjustment inertia weight immune particle swarm optimization(EAIW-IPSO)to enhance the accuracy and reliability regarding the selection of shield tunneling parameter values.Accordin...This article proposes an exponential adjustment inertia weight immune particle swarm optimization(EAIW-IPSO)to enhance the accuracy and reliability regarding the selection of shield tunneling parameter values.According to the iteration changes and the range of inertia weight in particle swarm optimization algorithm(PSO),the inertia weight is adjusted by the form of exponential function.Meanwhile,the self-regulation mechanism of the immune system is combined with the PSO.12 benchmark functions and the realistic cases of shield tunneling parameter value selection are utilized to demonstrate the feasibility and accuracy of the proposed EAIW-IPSO algorithm.Comparison with other improved PSO indicates that EAIW-IPSO has better performance to solve unimodal and multimodal optimization problems.When solving the selection of shield tunneling parameter values,EAIW-IPSO can provide more accurate and reliable references for the realistic engineering.展开更多
基金The authors are grateful for the support provided by the Co-fundingof National Natural Science Foundation of China and Shenhua Group Corporation Ltd(Grant No. U1261212) and the Program of Major Achievements Transformation andIndustrialization of Beijing Education Commission (Grant No. ZDZH20141141301).
文摘This article proposes an exponential adjustment inertia weight immune particle swarm optimization(EAIW-IPSO)to enhance the accuracy and reliability regarding the selection of shield tunneling parameter values.According to the iteration changes and the range of inertia weight in particle swarm optimization algorithm(PSO),the inertia weight is adjusted by the form of exponential function.Meanwhile,the self-regulation mechanism of the immune system is combined with the PSO.12 benchmark functions and the realistic cases of shield tunneling parameter value selection are utilized to demonstrate the feasibility and accuracy of the proposed EAIW-IPSO algorithm.Comparison with other improved PSO indicates that EAIW-IPSO has better performance to solve unimodal and multimodal optimization problems.When solving the selection of shield tunneling parameter values,EAIW-IPSO can provide more accurate and reliable references for the realistic engineering.
