Benchmarking numerical and agent-based models of an oil refinery supply chain

Today's integrated refinery supply chains embrace two distinct types of complexities (i) a complex production processes that can operate in various regimes, handling different raw materials and producing a variety of products, and (ii) a complex network of intelligent plan-source-move type elements that synchronize among the far-flung supply chain entities to ensure smooth, efficient, and profitable operation. Modelling such socio-technical systems poses a significant challenge. Traditionally numerical modelling has been the preferred choice, especially in process systems engineering; but recently agent-based modelling, which take an actor-centric perspective, has begun to be considered as an alternative. In this paper, we critically evaluate the choice of modelling paradigms for an integrated oil refinery supply chain. Initial experiments confirm that the behaviour of the two models is the same - thus validating the conjecture that a problem can be adequately described in both paradigms. The equation-based model appears to be better suited for describing complex physical and chemical phenomena; the agent-based model allows efficient ways to describe actions and behaviours of human and decision-making elements where cooperation and negotiation between intelligent entities come to the fore.