Robust Scheduling of Crude Oil Operations under Demand and Ship Arrival Uncertainty

Scheduling of crude oil operations is an important and complex routine task in a refinery. It involves crude oil unloading, tank allocation, storage and blending of crudes, and CDU charging. Optimal crude oil scheduling can increase profits by exploiting cheaper but poor quality crudes, minimizing crude changeovers, avoiding ship demurrage, and managing crude inventory optimally. In our previous work (Li et al. 2005), we have developed robust algorithms for obtaining optimal schedules for operations without any uncertainty. However, in a practice, uncertainties are unavoidable. Some common and frequent uncertainties in refinery operations include ship arrival delays, demand fluctuations, equipment malfunction, etc. In the face of these uncertainties, an optimal schedule obtained using nominal parameter values may often be suboptimal or even become infeasible. Thus, it is critical to develop algorithms that can consider future uncertainty at the scheduling stage to improve schedule feasibility and robustness. So far, scheduling and planning under uncertainty has been studied in specific fields such as capacity expansion, production planning, batch plant scheduling, etc. Demand and processing time uncertainties have been the focus of most existing work in the batch area. However, little work exists on refinery planning and scheduling under uncertainty. Arief et al. (2004) proposed a heuristic approach to reschedule operations of a given schedule to accommodate disruptions. Neiro and Pinto (2005) proposed a production-planning model incorporating product price and demand uncertainties in a refinery. Li et al. (2004) addressed the problem of refinery planning under demand or other economic parameters uncertainties with two-stage stochastic programming approach. Li et al. (2005) developed a planning model for refinery under correlated and truncated price and demand uncertainties. However, no work has so far addressed the development of robust schedules for crude oil scheduling in the face of uncertainties. Therefore, in this paper, we modify the deterministic MILP approach of Reddy et al. (2004b) to address two important uncertainties in crude operations, namely product demand and ship arrival uncertainties and develop some strategies to obtain robust schedules.