In oil sands mining, timely provisions of ore and tailings containment with less environmental footprints are the main drivers of profitability and sustainability. The recent Alberta Energy Resources Conservation Board Directive 074 requires oil sands waste disposal planning to be an integral part of mine planning. This requires the development of a well integrated strategy of directional mining and tailings dyke construction for in-pit and ex-pit tailings storage management. The objectives of this paper are to: 1) determine the order and time of extraction of ore, dyke material and waste that maximizes the net present value; 2) determine the destination of dyke material that minimizes construction cost; and 3) minimize deviations from the production goals of the mining operation. We have developed, implemented, and verified a theoretical optimization framework based on mixed integer linear goal programming (MILGP) to address these objectives. This study presents an integration of mixed integer linear programming and goal programming in solving large scale mine planning optimization problems using clustering and pushback techniques. Application of the MILGP model was presented with an oil sands mining case. The MILGP model generated a smooth and uniform mining schedule that generates value and provides a robust framework for effective waste disposal planning. The results show that mining progresses with an ore to waste ratio of 1:1.5 throughout the mine life, generating an overall net present value of $14,237M. This approach improves the sustainable development of oil sands through better waste management
