Long-term production scheduling of open pit mines using particle swarm and bat algorithms under grade uncertainty

A Khan

doi:10.17159/2411-9717/2018/v118n4a5

Abstract

Long-term production scheduling of open pit mines using particle swarm and bat algorithms under grade uncertainty

Highlights

Long-term production scheduling for open pit mines is a large-scale, complex optimization problem involving large data-sets, multiple hard and soft constraints, and uncertainty in the input parameters
Different stochastic programming models have been proposed in recent years to integrate this grade uncertainty into the optimization process, but solving these models for actual-sized open pit mines is usually extremely difficult and computationally expensive
Two different computationally efficient population-based metaheuristic techniques based on particle swarm optimization (PSO) and the bat algorithm are used to solve one particular stochastic variant of the open pit mine scheduling problem, i.e. the twostage stochastic programming model with recourse for determining the longterm production schedule of an open pit mine under the condition of grade uncertainty

Summary

Introduction

Long-term production scheduling for open pit mines is a large-scale, complex optimization problem involving large data-sets, multiple hard and soft constraints, and uncertainty in the input parameters.

Results

Conclusion