煤矿节能减排多目标优化研究

Research on multi-objective optimization of coal mine energy saving and emission reduction

针对传统煤矿节能减排优化模型选取的目标函数比较单一的问题,构建了涵盖经济效益、能源消耗、污染物排放量等目标函数的煤矿节能减排多目标优化模型,并应用基于改进的蝙蝠算法寻找3个目标函数之间的优化解,实现了经济效益最大化、能源消耗最低化、污染物排放量最少化的优化结果。仿真结果表明,相比于PSO-E、NSGA-II算法,改进的蝙蝠算法能够在较短的迭代步数内获取较高的个体适应度,且能够实现较佳的多目标优化结果,符合节能规划的目标需求。

In view of problem of single objective function existed in traditional optimization model of coal energy saving and emission reduction, a multi-objective optimization model of coal mine energy saving and emission reduction was established, which contains objective functions of economic benefits, energy consumption and pollutant emissions. Improved bat algorithm was applied to look for the optimization solution among three objective functions, so as to achieve the optimization results of the maximization of the economic benefits, the minimization of energy consumption and the minimization of pollutant emissions. The simulation results show that the improved bat algorithm can obtain a higher individual fitness within shorter iteration steps, and can achieve better multi-objective optimization results and meet target demand of the energy saving plan compared with PSO-E, the NSGA-II algorithm.