针对水库群供水优化调度问题,建立改进蚁群算法求解带罚函数的水库群供水优化调度数学模型,重点研究蚁群算法的改进。在对传统蚁群算法研究的基础上,提出一种自适应调整信息素挥发系数、信息量及转移概率的改进蚁群算法,克服传统蚁群算法收敛速度慢且容易陷入局部极值等方面的缺陷,并将其应用于黑河三水库联合供水优化调度中。与传统蚁群算法优化结果的比较表明,应用改进蚁群算法的优化调度结果较传统蚁群算法更为合理,该算法有利于提高计算效率、优化质量及改善收敛性能,为解决水库群供水优化调度问题提供了新方法。
A mathematical model with a penalty function was developed to solve optimization problems with multiple constraints in the dispatching of reservoir group water supply by using an improved ant colony algorithm, focusing on the method of improvement. This improved algorithm is featured with self-adaptive adjustment in pheromone evaluation coefficient, information quantity, and transition probability, and it can overcome the defects of traditional ant colony algorithm in slow convergence and local-extremum trapping. Its application to the three reservoirs on the Hei River achieved optimal scheduling schemes better than traditional ant colony algorithm. The improved algorithm is better in computational efficiency, optimization results, convergence, and it provides a new approach to optimization of reservoir group water supply dispatching.