NLP与GA在煤矿开采进度计划中的比较应用

The comparison Between NLP and GA used in Optimizing the Project Scheduling in Coal Mining

本文运用非线性规划(NLP)和遗传算法(GA)在网络图优化的基础上,以净现值NPV(Net Present Value)最大化作为进度安排目标,分别对平安五矿己二采区首采面开工的进度计划进行二次优化控制。结果表明本文提出的GA要优于NLP并且优化后净现值比NLP多60000元。

In this paper, non-linear programming （NLP）and genetic algorithm （GA） are used in optimizing the project scheduling of the second region of the first coal face of the fifth Ping’an Coa of which the objective is the maximal NPV （Net Present Value）l. The optimizing results show that GA is better than NLP and the NPV based on optimized operations is more than NLP 60000 RMB.