Pattern search method for accelerating Stope boundary optimization problem in underground mining operations

The Stope Boundary Optimization (SBO) problem refers to the layout design of production areas (stopes) in an underground mining operation. It falls within the domain of strategic mine planning and a model that addresses this problem aims to maximize profitability, offers optimal management of mineral resources and facilitates decision making around capital investments. The SBO problem is computationally complex and a method that offers solution within a reasonable computation time does not exist. In this article, a combination of a new greedy algorithm and a pattern search technique with an integer programming model is proposed. An implementation of the proposed method on three realistic case studies confirms its efficiency in generating robust solutions with a better optimality gap and considerably less computational effort.

Automated summary

The Stope Boundary Optimization (SBO) problem addresses the layout design of production areas in underground mining for maximizing profitability and optimal mineral resource management. A new model combining a greedy algorithm and pattern search technique with integer programming was proposed and shown to generate robust solutions with a better optimality gap in realistic case studies.