Abstract
We introduce a periodic supply vessel planning problem under demand and weather uncertainty, arising in the logistics operations for offshore oil and gas production. The problem arises in upstream offshore logistics, where supply vessels are the most expensive resource. In this problem, a fleet of supply vessels delivers materials and equipment to a set of offshore installations on a periodic basis from an onshore supply base. The aim is to determine an optimal fleet composition and a least-cost vessel schedule repeatedly applied over a certain execution horizon.
The challenge is that the performance of the vessel schedule is affected by uncertain demand at the installations and by uncertain weather conditions, which influence both the sailing and service times, leading to delays. Uncertainties may create an inability to serve all installations on a planned voyage due to insufficient vessel capacity or excessive voyage duration. These two types of uncertainty jointly result in modifications of the sailing schedule at the operational level with additional unplanned voyages where, in the worst case, extra vessels must be hired at a high cost. The logistics planners aim to create a vessel schedule of least expected cost over the schedule execution horizon.
We impose reliability requirements accounting for both demand and weather uncertainty and present an optimization-simulation algorithm incorporating the simulation model within the metaheuristic for the construction of schedules with different levels of reliability which, applied iteratively for the increasing values of reliability level parameters, yields a vessel schedule of least expected cost for large-size instances of a real-life supply vessel planning problem with combined uncertain demands and weather conditions.
Literature:
|
1. Kisialiou, Y., Gribkovskaia, I., Laporte, G. Periodic supply vessel planning under demand and weather uncertainty, INFOR: Information Systems and Operational Research, 59:3, 411-438, 2021. 2. Y. Kisialiou, I. Gribkovskaia and G. Laporte. Supply vessel routing and scheduling under uncertain demand, Transportation Research Part C, 104, 305-316, 2019. 3. Y. Kisialiou, I. Gribkovskaia and G. Laporte. Robust supply vessel routing and scheduling,Transportation Research Part C, 90, 366-378, 2018. |
|
4. Y. Kisialiou, I. Gribkovskaia and G. Laporte. The periodic supply vessel planning problem with flexible departure time and coupled vessels, Computers and Operations Research, 94, 52-64, 2018. |
|
5. E.K. Norlund, I. Gribkovskaia and G. Laporte. Supply vessel planning under cost, environment and robustness considerations, Omega, 57, 271-281, 2015. |
About the speaker:
Irina Gribkovskaia is currently a Professor of Quantitative Logistics. She has a PhD in Differential Equations from the Belarusian State Uni- versity (1997). Prior to becoming a professor in 2008, Irina worked as an Associate Professor at the Faculty of Applied Mathematics, Be- larusian State University and at Molde University College. Her main research interests are mathematical modeling and optimization meth- ods for planning problems, planning under uncertainty, vehicle routing, and offshore energy logistics.