A MILP model for planning the trips of dynamic positioned tankers with variable travel time

The transportation of the crude oil produced in offshore oilfields to onshore terminals is performed by vessels, known as shuttle tankers. Scheduling shuttle-tanker operations entails solving complex problems to ensure a timely offloading of the platforms, taking into account several logistics and inventory constraints. This work proposes a new MILP formulation that advances previous works by considering variable travel time between platforms and terminals. The combination of the MILP formulation with an optimization solver constitutes a decision-support tool to aid engineers reach optimal decisions for a planning horizon. To handle large-scale instances, rolling-horizon and relax-and-fix strategies are proposed.     

A continuous time model for multiple yard crane scheduling with last minute job arrivals

Container terminal (CT) operations are often bottlenecked by slow YC (yard crane) movements. Efficient YC scheduling to reduce the PM waiting time is therefore critical in increasing a CT's throughput. This paper develops an efficient continuous time MILP model for YC scheduling. The model treats realistic operational constraints such as multiple inter-crane interference, fixed YC separation distances, simultaneous container storage/retrievals, realistic YC acceleration/deceleration stages and gantry time, and require far fewer integer variables than previous work. The model significantly improves the solution quality compared to the existing discrete time models and other heuristics found in the literature. Using heuristics and a rolling-horizon algorithm, our model can solve actual container yard (CY) problems quickly and robustly in polynomial time. Also, to cope with the last minute container arrivals which can disrupt routine CT operations, two methods for handling these last minute job insertions are discussed and compared.