| 摘 要: 近年来，国家对高校实验室教学平台共享的要求逐步提高，如何低能耗开放和规划实验室利用是非常有意义的研究。为充分利用随机微粒群算法的强局部搜索力和单纯形法的多样性，提出了一种改进的基于单纯形法的随机微粒群算法，通过数值实验证明算法的有效性，并以实验室电量优化为目标进行仿真，实验表明本文算法能有效减少电量消耗。 |
| 关键词: 实验室规划；随机微粒群算法；单纯形法 |
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中图分类号: TP301.6
文献标识码: A
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| Research on Open Laboratory Planning based on Stochastic Particle Swarm Optimization |
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WANG Jianli
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(School of Computer Science and Technology, Taiyuan University of Science and Technology, Taiyuan 030024, China)
wangjianli@tyust.edu.cn
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| Abstract: In recent years, China has gradually increased the requirements for the sharing of university laboratory teaching platforms. How to open and plan laboratory utilization with low energy consumption is a very meaningful research. In order to make full use of the strong local search power of the stochastic particle swarm optimization and the diversity of the simplex algorithm, this paper proposes an improved stochastic particle swarm optimization based on the simplex algorithm. Numerical experiments show the effectiveness of the algorithm. Simulation is carried out with the goal of laboratory power optimization. Experiments show that the proposed algorithm can effectively reduce power consumption. |
| Keywords: laboratory planning; stochastic particle swarm optimization; simplex algorithm |
