摘要
矿产资源不可再生,应尽量开采低品位矿石以充分利用矿产资源,但低品位矿石会损害企业的经济效益。因此,如何合理确定矿山的矿石工业品位,达到延长企业寿命,充分利用资源,经济效益较优的目标具有非常重要的意义。论文基于矿山企业多目标优化的特性,利用粒子群算法(particle swarm optimization algorithm,PSO)对矿山企业多目标生产经营参数进行了优化。实现了对沃溪坑口的工业品位、开采规模、效益等多目标动态优化,为矿山企业生产提供了决策依据。
It is essential to make full use of mineral resources because it is Non-renewable. But low-grade ore would undermine economic efficiency of enterprises. Therefore, how to rationally determine the industrial grade ore mine, to extend the corporate life, full use of resources, highly profitable on economic objectives become very urgency, based on mining enterprises characteristics of multi-objective optimization, particle swarm optimization algorithm is adopt to optimize the multi-objective production parameters of mining enterprises, multi-objective parameter optimization PSO-based algorithm is proposed for production parameters for JinXin Gold Corporation, The multi optimization object such as mining grade, scale and gains can be get by PSO algorithm which provide a basis for decision making.
出处
《微计算机信息》
2010年第18期19-20,75,共3页
Control & Automation
关键词
多目标优化
PSO
参数优化
品位
经济评价
Multi-objective optimization
PSO
Parameter optimization
grade
economic evaluation
