用粒子群算法优化编制露天矿生产作业计划

Optimization of open-pit-mining operational planning by using a particle swarm algorithm

从露天矿采掘和运输成本的最小化角度出发,构建露天矿生产作业计划模型.基于群体智能优化理论,提出了用粒子群算法对露天矿生产作业计划模型进行解算的方法,并在求解过程中设计了带核粒子及双吸引子的粒子搜索策略.以MATLAB软件为平台进行求解运算最佳作业计划.以某露天铁矿为工程背景进行实例研究,将研究结果与露天矿实际生产指标和非线性规划解算结果进行比较验证.结果表明,粒子群算法可用于露天矿生产作业计划的优化编制.

A open-pit-mining operational planning model was constructed from the view point of minimizing the mining and transportation cost. Based on the theory of swarm intelligence optimization, a method was proposed that uses a particle swarm optimization （PSO） algorithm to optimize the open-pit mining operation plan, and a search strategy with the core particle and double attractor was designed for particles in the calculation process. The optimal operation plan was calculated by using MATLAB software as a computation platform. A case study was performed by taking an open-pit iron mine as an engineering background. By comparing the optimization results of the PSO algorithm with the actual planning results and the calculated results of nonlinear programming, it is proved that the PSO algorithm is feasible and reliable for optimizing the open-pit mining operation plan.