Application of Hybrid Particle Swarm Algorithm for Water Supply Optimization Scheduling in Mountain Scenic Spot

作者：Li, Jie^*; Huang, Yi; Li, Qiang; Zhu, Shan Shan; Ling, Liang; Fang, Cheng

来源：5th International Conference on Measurement, Instrumentation and Automation (ICMIA), China,Guangdong,Shenzhen, 2016-09-17 to 2016-09-18.

• particle swarm algorithm
• penalty method
• non-linear constrain
• optimization scheduling
• objective function
• optimal solution

As the characteristics of mountain scenic spot possess complicated topography, great elevation differences, high water diversion costs, limited reservoir storage capacity, uneven distribution of rainfall, coupled with hysteresis nature of the manual diversion, scarcity of water resources has become a major factor restricting the development of scenic spots. Therefore, it is an effective way to solve the water shortage problem through optimizing the existing water supply scheduling scheme. Water supply optimization scheduling in mountain scenic spot is a typical non-linear, in-differentiable, constraint problem. This paper aims at the problem of water supply optimization scheduling in mountain scenic spot and introduces a method to solve the hybrid particle swarm algorithm of nonlinear constrained optimization. The algorithm combines the advantages of penalty method and particle swarm optimization algorithms, employs particle swarm algorithm to solve complex objective function, and utilizes penalty method to introduce evaluation mechanism of penalty factor to deal with the constraint problem. In the end, this will be applied in water supply optimization scheduling of Huangshan Scenic Area. Experimental results demonstrate that the algorithm shows good performance in solving the water supply scheduling problem of mountain scenic spot.

• 出版日期2016
• 单位合肥工业大学