Novel modelling and decomposition strategy for total site optimisation

Abstract

Overall plant optimisation is one of the most difficult problems in the field of applied optimisation due to the size and mathematical complexity of the problem. The state-of-the-art approaches mainly rely on linear programming or mixed integer linear programming. Developing and solving rigorous site-wide models is still at research stage. In this work, a novel decomposition strategy is presented to tackle large-scale total site optimisation problems. This decomposition approach is derived from analysis of the mathematical structure of a general total site model, which features an angular structure with common elements and independent elements. This understanding forms the basis for decomposing the overall plant model into two levels, namely a site level (master model) and a process level (submodels). The master model determines common issues among processes, such as allocation of raw materials and utilities, etc. With these common issues determined, submodels then optimise individual processes. The results from submodel optimisation are fed back to the master model for further optimisation. This procedure terminates when convergence criteria are met. In this way, individual process optimisations are effectively controlled and co-ordinated by the centre master model. Case studies are carried out to demonstrate the effectiveness of the approach.