Parallel-machine flow shop scheduling with lot streaming techniques and its application to the mining industry

In open-pit mining, a trade-off between determination of appropriate sizes of mining jobs and optimisation of allocating and sequencing mining equipment units at each operational stage is one of critical decisions for mining practitioners. To simultaneously optimise the above data-driven interplay between planning and scheduling decisions in multi-stage mine production timetabling, we introduce a novel integrated-planning-scheduling problem for considering the variability of jobs’ sizes based on the theory of parallel-machine flow shop scheduling with lot streaming. This new problem is termed “Multi-stage Mine Production Timetabling with Optimising the Sizes of Mining Operations (MMPT-OSMO)”, in which the sizes of mining operations are considered as planning-type variables and integrated with scheduling-type variables in a parallel-machine flow shop scheduling system. By integrating both planning and scheduling decision variables in such a solitary problem, the MMPT-OSMO intrinsically characterises the potential to significantly improve mining productivity, which is validated by theoretical analysis and extensive computational experiments. The proposed MMPT-OSMO methodology would make a breakthrough in the field of mining optimisation, as it contributes to extend mathematical modelling boundary by applying continuous-time machine scheduling theory to operational-level mining optimisation in theory and to help mining practitioners improve the production throughput using lot-streaming techniques in practice.