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第40届中国控制会议

作者： Zhihao Yu Jialu Du Guangqiang Li School of Marine Electrical Engineering Dalian Maritime University

The intelligent optimization algorithm performs well in solving complex optimization problems in engineering. However, the intelligent optimization algorithm usually takes long execution time and large memory usage, which is not suitable for the engineering with limited hardware conditions. To handle this difficulty, in this paper, a novel compact harris hawks optimization（cHHO） algorithm is proposed, which is an modified version of the harris hawks optimization（HHO） algorithm. The cHHO algorithm searches the optimal solution using only one hawk, instead of a whole swarm of hawks in the HHO algorithm,by means of the compact optimization theory. Numerical experiments based on two commonly used benchmark functions show that the execution time of the cHHO algorithm is shorter and the memory usage is smaller, comparing with the HHO algorithm and the compact particle swarm optimization algorithm. Further, the c HHO algorithm is employed to the thrust allocation of a dynamic positioning vessel, and the simulation illustrates the effectiveness of the cHHO algorithm.

关键词： Harris Hawks optimization Algorithm compact optimization Thrust Allocation

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compact Differential Evolution Light: High Performance Despite Limited Memory Requirement and Modest Computational Overhead

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Journal of Computer Science & Technology 2012年第5期27卷 1056-1076页

作者： Giovanni Iacca Fabio Caraffini Ferrante Neri EDepartment of Mathematical Information Technology University of JyvskylP.O.Box 35(Agora) Department of Mathematical Information Technology University of JyvskylP.O.Box 35(Agora)

compact algorithms are Estimation of Distribution Algorithms which mimic the behavior of population-based algorithms by means of a probabilistic representation of the population of candidate solutions. These algorithms have a similar behaviour with respect to population-based algorithms but require a much smaller memory. This feature is crucially important in some engineering applications, especially in robotics. A high performance compact algorithm is the compact Differential Evolution （cDE） algorithm. This paper proposes a novel implementation of cDE, namely compact Differential Evolution light （cDElight）, to address not only the memory saving necessities but also real-time requirements, cDElight employs two novel algorithmic modifications for employing a smaller computational overhead without a performance loss, with respect to cDE. Numerical results, carried out on a broad set of test problems, show that cDElight, despite its minimal hardware requirements, does not deteriorate the performance of cDE and thus is competitive with other memory saving and population-based algorithms. An application in the field of mobile robotics highlights the usability and advantages of the proposed approach.

关键词： differential evolution compact optimization real-time optimization

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