超导磁储能系统(superconducting magnetic energy storage,SMES)是超导应用研究的热点。SMES利用超导磁体的低损耗和快速响应能力,通过电力电子型变流器与电力系统相连,组合为一种既能为其储存电能又能为其释放电能的多功能电磁系统。S...超导磁储能系统(superconducting magnetic energy storage,SMES)是超导应用研究的热点。SMES利用超导磁体的低损耗和快速响应能力,通过电力电子型变流器与电力系统相连,组合为一种既能为其储存电能又能为其释放电能的多功能电磁系统。SMES的先进功能主要体现于,它能大容量超低损耗的储存电能、改善供电质量、提高系统的稳定性和可靠性。该文以SMES的优化设计(IEEE TEAM Workshop Problem 22)为例,介绍了序贯优化方法和克里金(Kriging)统计近似模型在低维和高维、离散域和连续域优化问题中的应用。优化结果显示,该优化方法能在保证设计精度的前提下,极大降低有限元的计算量。如3参数优化问题中有限元的计算量比直接优化的1/10还要少;而8参数优化问题中有限元的计算量约为直接优化的1/3。从而该方法可广泛应用于电磁装置的优化设计问题。展开更多
Constrained optimization problems are very important as they are encountered in many science and engineering applications.As a novel evolutionary computation technique,cuckoo search(CS) algorithm has attracted much at...Constrained optimization problems are very important as they are encountered in many science and engineering applications.As a novel evolutionary computation technique,cuckoo search(CS) algorithm has attracted much attention and wide applications,owing to its easy implementation and quick convergence.A hybrid cuckoo pattern search algorithm(HCPS) with feasibility-based rule is proposed for solving constrained numerical and engineering design optimization problems.This algorithm can combine the stochastic exploration of the cuckoo search algorithm and the exploitation capability of the pattern search method.Simulation and comparisons based on several well-known benchmark test functions and structural design optimization problems demonstrate the effectiveness,efficiency and robustness of the proposed HCPS algorithm.展开更多
A novel hybrid algorithm named ABC-BBO, which integrates artificial bee colony(ABC) algorithm with biogeography-based optimization(BBO) algorithm, is proposed to solve constrained mechanical design problems. ABC-BBO c...A novel hybrid algorithm named ABC-BBO, which integrates artificial bee colony(ABC) algorithm with biogeography-based optimization(BBO) algorithm, is proposed to solve constrained mechanical design problems. ABC-BBO combined the exploration of ABC algorithm with the exploitation of BBO algorithm effectively, and hence it can generate the promising candidate individuals. The proposed hybrid algorithm speeds up the convergence and improves the algorithm's performance. Several benchmark test functions and mechanical design problems are applied to verifying the effects of these improvements and it is demonstrated that the performance of this proposed ABC-BBO is superior to or at least highly competitive with other population-based optimization approaches.展开更多
The traditional manner to design public transportation system is to sequentially design the transit network and public bicycle network. A new public transportation system design problem that simultaneously considers b...The traditional manner to design public transportation system is to sequentially design the transit network and public bicycle network. A new public transportation system design problem that simultaneously considers both bus network design and public bicycle network design is proposed. The chemical reaction optimization(CRO) is designed to solve the problem. A shortcoming of CRO is that, when the two-molecule collisions take place, the molecules are randomly picked from the container.Hence, we improve CRO by employing different mating strategies. The computational results confirm the benefits of the mating strategies. Numerical experiments are conducted on the Sioux-Falls network. A comparison with the traditional sequential modeling framework indicates that the proposed approach has a better performance and is more robust. The practical applicability of the approach is proved by employing a real size network.展开更多
文摘超导磁储能系统(superconducting magnetic energy storage,SMES)是超导应用研究的热点。SMES利用超导磁体的低损耗和快速响应能力,通过电力电子型变流器与电力系统相连,组合为一种既能为其储存电能又能为其释放电能的多功能电磁系统。SMES的先进功能主要体现于,它能大容量超低损耗的储存电能、改善供电质量、提高系统的稳定性和可靠性。该文以SMES的优化设计(IEEE TEAM Workshop Problem 22)为例,介绍了序贯优化方法和克里金(Kriging)统计近似模型在低维和高维、离散域和连续域优化问题中的应用。优化结果显示,该优化方法能在保证设计精度的前提下,极大降低有限元的计算量。如3参数优化问题中有限元的计算量比直接优化的1/10还要少;而8参数优化问题中有限元的计算量约为直接优化的1/3。从而该方法可广泛应用于电磁装置的优化设计问题。
基金Projects([2013]2082,[2009]2061)supported by the Science Technology Foundation of Guizhou Province,ChinaProject([2013]140)supported by the Excellent Science Technology Innovation Talents in Universities of Guizhou Province,ChinaProject(2008040)supported by the Natural Science Research in Education Department of Guizhou Province,China
文摘Constrained optimization problems are very important as they are encountered in many science and engineering applications.As a novel evolutionary computation technique,cuckoo search(CS) algorithm has attracted much attention and wide applications,owing to its easy implementation and quick convergence.A hybrid cuckoo pattern search algorithm(HCPS) with feasibility-based rule is proposed for solving constrained numerical and engineering design optimization problems.This algorithm can combine the stochastic exploration of the cuckoo search algorithm and the exploitation capability of the pattern search method.Simulation and comparisons based on several well-known benchmark test functions and structural design optimization problems demonstrate the effectiveness,efficiency and robustness of the proposed HCPS algorithm.
基金Projects(61463009,11264005,11361014)supported by the National Natural Science Foundation of ChinaProject([2013]2082)supported by the Science Technology Foundation of Guizhou Province,China
文摘A novel hybrid algorithm named ABC-BBO, which integrates artificial bee colony(ABC) algorithm with biogeography-based optimization(BBO) algorithm, is proposed to solve constrained mechanical design problems. ABC-BBO combined the exploration of ABC algorithm with the exploitation of BBO algorithm effectively, and hence it can generate the promising candidate individuals. The proposed hybrid algorithm speeds up the convergence and improves the algorithm's performance. Several benchmark test functions and mechanical design problems are applied to verifying the effects of these improvements and it is demonstrated that the performance of this proposed ABC-BBO is superior to or at least highly competitive with other population-based optimization approaches.
基金Projects(71301115,71271150,71101102)supported by the National Natural Science Foundation of ChinaProject(20130032120009)supported by Specialized Research Fund for the Doctoral Program of Higher Education of China
文摘The traditional manner to design public transportation system is to sequentially design the transit network and public bicycle network. A new public transportation system design problem that simultaneously considers both bus network design and public bicycle network design is proposed. The chemical reaction optimization(CRO) is designed to solve the problem. A shortcoming of CRO is that, when the two-molecule collisions take place, the molecules are randomly picked from the container.Hence, we improve CRO by employing different mating strategies. The computational results confirm the benefits of the mating strategies. Numerical experiments are conducted on the Sioux-Falls network. A comparison with the traditional sequential modeling framework indicates that the proposed approach has a better performance and is more robust. The practical applicability of the approach is proved by employing a real size network.
