We consider a scheduling problem faced by a shipping company that provides lightering services to multiple refineries clustered in a region. The company operates a fleet of multi-compartment lightering vessels with a mix of different configurations such as numbers of compartments, sizes, speeds, heating equipment, and so on. When a tanker arrives at the lightering location, one lightering vessel pumps off crude oil from one side of the tanker. Therefore, at most two lightering services can take place simultaneously for a tanker, one at each side of the tanker. And, these multi-compartment lightering vessels can pick up multiple types of crude from the same/different tankers during a voyage. After enough crude oil has been offloaded, the tanker leaves the lightering system and travels to its designated refinery port. However, lightering vessels travel to the refinery ports, deliver the crude oils, and then return to the lightering location to continue their service. In other words, the lightering vessels make multiple voyages among the refinery ports and lightering location in order to service multiple tankers. Furthermore, we consider a two-stage lightering practice for large tankers, first stage at an offshore location farther from the refinery and the second stage at the lightering location closer to the refinery. Chajakis (1997) has described this problem in detail, while Lin et al. (2003) addressed a limited form of the same using an event-based approach. They assumed single-compartment vessels, did not restrict the number of simultaneous services for a single tanker, did not allow pickups from more than two tankers within one voyage of a lightering vessel, ignored differences in crude densities, and did not allow the freedom to select lightering crudes. In this paper, we develop a new continuous-time MILP formulation that addresses all of the above drawbacks. Thus, we allow multi-compartment lightering vessels, restrict the number of simultaneous transfers to two, allow more than two pickups in one voyage for any lightering vessel, consider the impact of varying crude densities, select optimally the right lightering crudes, and most importantly use a realistic cost-based scheduling objective. Often, these features are real and important in the tank lightering problem. In contrast to the general chemical transshipment problem, the volumes and assignments to lightering vessels in this case are decided by the optimization model. In addition, the system cost here is an indicator of the customer satisfaction level as well as the utilization of fleet of lightering vessels. Our MILP model generates optimal lightering schedule with lightering volumes, sequence, times, and assignments, which minimizes the operating costs of lightering vessels, the demurrage costs of tankers as well as the delivery times of crude oil from the lightering location to refinery ports. We compare the performance of reduced versions of our general lightering models with those of Lin et al. (2003) using their example problems. In addition, we solve several more general examples to illustrate the application of our general model to the tanker lightering problem.
Keywords: transshipment operations, scheduling, tanker lightering, shipping, maritime transportation
References:
(1) Chajakis, E. D. (2000). Management science for marine petroleum logistics. In Decision making: recent developments and worldwide applications; Zanakis, S. H., Doukidis, G., Zopounidis, C., Eds.; Kluwer academic publishers: Dordrecht, the Netherlands, 279-292.
(2) Chajakis, E. D. (1997). Sophisticated crude transportation. OR/MS Today. (Dec), 24.
(3) Lin, X., Chajakis, E. D., Floudas, C.A. (2003). Scheduling of tanker lightering via a novel continuous-time optimization framework. Ind. Eng. Chem. Res. 42, 4441-4451.
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