Determination of the optimum pit economic value and the 2-D sectional pit design using A.I. search techniques

摘要

Surface mining is a very large scale operation involving huge capital expenditure. One of the major engineering design tasks in the development of a surface mine is the optimum pit design. Determining the optimum pit design and its pit value will aid the mining engineer in the feasibility assessment stage of the mining project. It also aids in designing good haul roads and in identifying that set of ore blocks which would yield maximum profit to the mining company. The complexity of the factors involved viz. geologic conditions, ore types, ore grade, ore tonnage, operating cost, desired profit, production rate, market conditions etc. makes optimum pit design a complex task to deal with. In this paper, the focus is on the application of A.I. heuristic search techniques to design the optimum pit of a surface mine. One of the most popular A.I. heuristic search methods is based on the utilization of the information incorporated in the structures of the solution points. These are popularly known as genetic algorithms. Genetic algorithms provide a very powerful mechanism for searching large solution spaces and possess an inherent capacity to incorporate complex constraints and have been widely used to effectively solve large scale optimization problems. Since, the set of mathematical equations that model the two dimensional optimum pit design problem define a very large solution space and is inherent with many constraints, genetic algorithms have been used to negotiate the design of the optimum pit.