Optimization of production planning in underground mining

Abstract

Use of Integer programming (IP) or mixed integer programming (MIP) for formulation of mine optimization problem is best suited modelling approach for underground mining. Optimization algorithm for underground stope design problems cannot be generalised as geotechnical constraints for each method is different. This project concentrates on optimization model for open stoping mining method. The stope design model maximizes Net cash flow of the stope while adhering to the stope constraints. The methodology considers open stoping sequence, in which every block is moved towards the cross-cuts at the lower level. In this thesis, stopes are designed to maximize the undiscounted cash flow from the stope after satisfying stope height and extraction angle constraints. An integer programming formulation is developed and solved using CPLEX solver for single stope. The proposed algorithm is solved for first stope and then blocks for the crown pillar for first stope is identified. After eliminating the first stope and respective crown pillar data from the data set, algorithm is solved again for the second stope from the remaining data set. After stope design, production scheduling is done by applying heuristic approaches. Blocks from the stopes are extracted heuristically satisfying extracting angle, mining and processing constraints. Initially blocks from the first stope are selected and then to fulfil the constraints, some of the blocks from the second stope are selected. A study is carried out on the part of the Zinc mine data of India which contains 4992 number of blocks. Total 3 numbers of stopes are designed. The NPV of the considered data is found to be 7313.346 million rupees in 3 periods with total tonnage of 1.103 million tonnes. Metal content in 3 periods is found to be 86.485 thousand Tonnes. The overall dilution is found to be 3.82% with average dilution of 2.692%