基于满意优化的氧化铝生料浆调配方法

Satisfactory optimization of raw slurry arrangement for process of alumina production

提出了基于多目标满意优化的生料浆调配智能优化方法.该方法以满意度函数反映决策者对性能指标的评价,以综合满意度函数反映决策者对多目标协调的要求,构建氧化铝生料浆调配的满意优化模型,并通过自适应调整交叉概率和变异概率的改进遗传算法求解满意优化问题.所得优化结果更能反映决策者对实际工艺指标的评价,大幅度提高计算效率,减少生料浆质量指标的波动.基于工业运行数据的计算结果表明了该方法的有效性和实用性.

A satisfactory optimization approach is proposed for the raw slurry arrangement in the process of alumina production. A satisfactory degree function based on the satisfaction degree of the decision-maker is defined to evaluate the performance of optimal objectives, and a synthesis satisfactory degree function is constructed to evaluate optimization results. The satisfactory optimization problem is solved by an improved genetic algorithm where the crossover rate and mutation rate are adjusted according to fitness function. The optimization results show that the computational efficiency is increased greatly, the composition fluctuation in mixed raw slurry is decreased a lot, and more satisfactory performances are achieved than that of traditional methods. The computation results based on the industrial data show the effectiveness and practicality of the proposed approach.