Open pit mine design and extraction sequencing by use of OR and AI concepts

Abstract

sequence of mining blocks over short periods of time, has become more desirable in today's competitive and high risk mining world with low commodity prices. There have been various unsuccessful attempts to develop such a procedure, using operations research (OR) methods. The main reasons for the failure of these attempts are inadequacy of OR methods to model fully an open pit operation and excessive computational requirements of solution procedures. This paper presents a technique that is based on the dynamic programming of OR and machine learning-expert system concepts of artificial intelligence (AI). This technique provides an extraction sequence of mining blocks that aims to maximize the next present value while satisfying all technical and economical constraints of an open pit mine operation. Case studies showed that this method provides an effective tool for the mine planning engineer to generate various extraction sequences for various economical and technical factors within very short computational time. The development of an effective open pit mine scheduling procedure which will generate and evaluate the extraction. © 1995, Taylor & Francis Group, LLC. All rights reserved.