Strategic mine planning and waste management are important aspects of surface mining operations. Due to the limitations in lease area for oil sands mining, the pit phase advancement is carried out simultaneously with the construction of in-pit and ex-pit tailings impoundment dykes. Most of the materials used in constructing these dykes come from the oil sands mining operation including overburden, interburden and tailings coarse sand.

The primary research objectives are to develop, implement and verify a theoretical optimization framework based on Mixed Integer Linear Goal Programming (MILGP) model to:​ 1) determine the time and order of extraction of ore, dyke material and waste that maximizes the net present value of the operation – a strategic schedule;​ 2) determine the destination of the dyke material that minimizes construction cost – a dyke material schedule. Matlab programming platform was chosen for the MILGP model framework implementation. A large scale optimization solver, Tomlab/CPLEX, is used for this research.

To verify the research models, four oil sands case studies were carried out. The first three case studies highlight the techniques and strategies used in the MILGP model to integrate waste disposal planning with production scheduling in oil sands mining. The fourth case study, which involves the scheduling of 16,985 blocks, was compared with industry standard software, Whittle. No waste disposal planning was considered since Whittle does not provide such tools. The MILGP model generated an optimal production schedule with a 13% higher NPV than Whittle Milawa NPV and a 15% higher NPV than Whittle Milawa Balanced case. In comparison, while Whittle deferred ore mining to latter years, the MILGP model scheduled for more ore in the early years contributing to the increased NPV. The experiments also compared the annual stripping ratio, average grade and annual production. These results proved that the MILGP model framework provides a powerful tool for optimizing oil sands long term production schedules whilst giving us a robust platform for integrating waste disposal planning.