基于自适应遗传算法的矿山设备系统优化

Mine Equipment System Optimization Based on Adaptive Genetic Algorithm

提出了基于自适应遗传算法的矿山装备系统优化算法模型,采用多参数级联符号编码,其变异率和交叉率可根据群体适应度自调整而具有更好的收敛效果和全局搜索能力。根据矿山设备系统的实际特点,对算法模型中的交叉率和变异率等关键算子和操作步骤作了较详细叙述。理论上分析了自适应遗传算法在解决此类问题上的可行性。矿山生产企业根据矿山设备系统优化模型的自适应遗传运算结果,优化设备系统,可以达到提高矿山投入产出比,有效提高矿山产能的目的。

The algorithm model for mine equipment system optimization was proposed on the basis of adaptive genetic algorithm.Multi-parameter cascade symbolic coding,mutation rate and cross rate are adopted.According to group fitness,mutation rate and cross rate with self-adjusting have a better convergence result and global searching ability.The key operators of mutation rate,cross rate etc. in the algorithm model,and its operation steps were explained detailedly.Feasibility of the adaptive genetic algorithm in solving such issues was theoretically analyzed.Mine enterprises can optimize equipment system based on the results of adaptive genetic operation.As a result,the input-output ratio and the mine productivity can be improved effectively.