Planning for Mining Operations with Time and Resource Constraints


  • Nir Lipovetzky The University of Melbourne
  • Christina Burt The University of Melbourne
  • Adrian Pearce The University of Melbourne
  • Peter Stuckey The University of Melbourne



Mixed-Integer Program, State-Dependent Network, Planning with Resources, Temporal Planning


We study a daily mine planning problem where, given a set of blocks we wishto mine, our task is to generate a mining sequence for the excavators suchthat blending resource constraints are met at various stages of thesequence. Such time-oriented resource constraintsare not traditionally handled well by automated planners. On the other hand,the remaining problem involves finding node-disjoint sequences withstate-dependent travel times on the arcs, which are highly challenging for a Mixed-Integer Program (MIP).In this paper, we address the problem of finding feasible sequences using a combined MIP and planning based decomposition approach. The MIP takes care of the resource constraints, and the planner solves the remaining sequence problem. We extend the notion of finding feasible sequences to finding good feasible sequences, by devising a heuristic objective function in the MIP, which improves the resulting search space for the planner.We empirically analyse the scalability of our approach on a benchmark data set, before demonstrating its effectiveness on a real world case study provided by our industry partner. These results demonstrate that by using a heuristic MIP, it is possible to obtain better makespan results with a suboptimal planner than by using an optimal planner with an uninformed MIP.




How to Cite

Lipovetzky, N., Burt, C., Pearce, A., & Stuckey, P. (2014). Planning for Mining Operations with Time and Resource Constraints. Proceedings of the International Conference on Automated Planning and Scheduling, 24(1), 404-412.