Open-pit mining is widely used to extract natural resources. Low cut-off grades and large operations can make open-pit mining profitable. An important challenge is to determine the optimum production schedule. Usually the goal is to maximize the net present value of the project while delivering ore to the plant at full capacity. The best production plan would require complete knowledge of the orebody and all other engineering and economic parameters. An estimated block model is often used to determine the production schedule. Uncertainty is inevitable with widely spaced drill holes. The open-pit production schedule based on estimated models may be suboptimal and affected dramatically by grade uncertainty. The research documented herein develops, implements and verifies four mixed integer optimization frameworks for long-term production scheduling in the presence of grade uncertainty. The main contributions of this research are (1) consideration of cost of grade uncertainty to influence the production plan, (2) accounting for the linear and nonlinear effects of the grade uncertainty on the long-term mine planning, (3) development of a mixed integer linear programming model that maximizes NPV and minimizes the cost of the grade uncertainty by considering a stockpile, and finally (4) implementation of a quadratic optimization model accounts for grade uncertainty in the long-term production plan.

This conference proceedings presents the research papers in the field of mine planning and mining equipment including themes such as mine automation, rock mechanics, drilling, blasting, tunnelling and excavation engineering. The papers presents the recent advancement and the application of a range of technologies in the field of mining industry. It is of interest to the professionals who practice in mineral industry including but not limited to engineers, consultants, managers, academics, scientist, and government staff.

This book presents a collection of papers on topics in the field of strategic mine planning, including orebody modeling, mine-planning optimization and the optimization of mining complexes. Elaborating on the state of the art in the field, it describes the latest technologies and related research as well as the applications of a range of related technologies in diverse industrial contexts.

This edited volume includes all papers presented at the 22nd International Conference on Mine Planning and Equipment Selection (MPES), Dresden, Germany, 2013. Mineral Resources are needed for almost all processes of modern life, whilst the mining industry is facing strict requirements regarding efficiency and sustainability. The research papers in this volume deal with the latest developments and research results in the fields of mining, machinery, automatization and environment protection.

The multi-period open pit mine production scheduling problem is formulated as a large scale linear programming problem using the block concept. A solution procedure is developed through decomposition and partitioning of the subproblem into elementary profit routing problems for which an algorithm is presented. Many of the traditional mine planning concepts are discussed and suggestions for improvement through use of the techniques developed in this thesis are given. In the development of the solution procedure, those constraints which govern the mining system are considered as the master problem. The constraints which dictate the sequence of extraction are used as the subproblem. The properties of the single period subproblem and its dual are discussed, and the dual problem is shown to be equivalent to a bipartite maximum flow problem for which an algorithm is given. The Multi-period subproblem algorithm is developed by partitioning by stages and using the properties of the single period subproblem. This treatment allows optimization of the complete mining-concentrating-refining system over the entire planning horizon and permits the system to dictate how and when to process a block of material. (Author).

Mine planning is a multi-disciplinary process that guides decision-making at all stages of the mining operation. Owing to inherent uncertainty, the planning process relies on engineering estimates and is iterative in nature. Mining operations utilize a variety of operations research-based applications to improve decision-making capabilities across all levels of planning. The intent of this work is to review past applications in the field of underground metalliferrous mine planning, modify existing optimization procedures to create more realistic long-term production schedules, and propose a new mathematical formulation for optimizing short-term schedules. In the past decade, better solution algorithms, improvedmodeling techniques, and availability of cheap computational power have driven greater research interest in the area of long-term decision-making analysis regarding underground mining method selection, cutoff grade, mine layout, open pit-underground transition, and equipment selection. Production schedule optimization has also seen significant advances with a number of researchers utilizing a Resource Constrained Project Scheduling Problem-based approach to create long-term schedules.