Abstract
Mine production scheduling serves to maximise the net present value of a mine by solving three interconnected sub-problems: a) extraction sequence of mining blocks; b) ore-waste discrimination; c) production rates. Even though potential of scheduling is well-recognised, some issues have not been resolved: 1) the sub-problems given above are solved in a sequential fashion rather than simultaneously that leads to sub-optimality; 2) the number of decision variables and constraints can easily be over millions. In this paper, a notion of memory is introduced into simulated annealing (SA) to solve such a large problem efficiently. A new heuristic memory is added to SA such that better search results are obtained faster. At each iteration, the heuristic and the objective function are recorded. If their correlation is high, heuristic is also incorporated into the objective function. A case study demonstrated the proposed method performs faster than the original simulated annealing algorithm.
Published Version
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