Yauhen Maisiuk

• Maisiuk, Yauhen & Gribkovskaia, Irina (2014). Fleet Sizing for Offshore Supply Vessels with Stochastic Sailing and Service Times. Procedia Computer Science. ISSN 1877-0509. 31, p. 939–948. doi: 10.1016/j.procs.2014.05.346. Show summary

  In this paper we address a supply vessel planning problem arising in servicing oil and gas offshore installations. Supply vessels provide offshore installations with necessary supplies on periodic basis from offshore supply bases according to weekly sailing schedules. The execution of weekly schedules during the year is affected by weather conditions influencing on sailing time and service duration at installations. When the contracted vessel cannot complete a voyage before the start of its next planned voyage, a vessel from the spot market is hired to perform it. Deciding on the number of supply vessels hired to perform operations from a supply base for a year ahead has a strong economic effect on the total annual vessel costs. We present a discrete-event simulation model for evaluation of alternative fleet size configurations taking into consideration uncertainty in weather conditions and future spot vessel rates. The model is validated and tested on real data.

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• Maisiuk, Yauhen & Gribkovskaia, Irina (2017). Evaluation of methods for construction of robust supply vessel schedules with discrete-event simulation. Show summary

  Supply vessel planning problem arises in offshore oil and gas logistics, where a fleet of vessels provides cargo deliveries to offshore installations on a periodic basis from an onshore supply base. The objective is to define an optimal fleet composition and a least-cost weekly sailing plan of scheduled vessels' voyages. The problem is defined as a fleet-sizing and periodic routing problem with multiple time windows at installations and voyage duration constraints. Weather conditions change dynamically and may significantly influence vessels' sailing and service times, resulting in sailing plan infeasibility. The planners need vessel plans with sufficient robustness to offset the impact of weather conditions and avoid use of additional vessels. Known approaches for construction of robust vessel schedules consist of generation of shortest duration voyages and solution of a set covering model. In some approaches, voyage slacks are incorporated during voyage generation phase based on planners' experience. In other approaches, shortest generated voyages are simulated over multiple replications of wave height evolution to compute voyage robustness measure or to assign voyage duration. In this study, we evaluate robustness of vessel schedules constructed by different robustness approaches with the developed discrete-event simulation model. It simulates weekly sailing schedules repetitively over seasonal horizon over multiple replications of weather scenarios. Multi-site multivariate seasonal sea state modeling is based on nonparametric numerical resampling and intra-day hind-cast metocean data. Experiments are conducted on real-based instances from an oil and gas company. We examine the impact of various instance characteristics on robustness of weekly sailing schedules.

• Maisiuk, Yauhen & Gribkovskaia, Irina (2015). Recourse strategies in weather dependent supply vessel operations.
• Gribkovskaia, Irina; Norlund, Ellen Karoline & Maisiuk, Yauhen (2014). Routing and fleet sizing for offshore supply vessels.
• Maisiuk, Yauhen & Gribkovskaia, Irina (2014). Fleet sizing for offshore supply vessels with stochastic sailing and service times.
• Gribkovskaia, Irina; Norlund, Ellen Karoline & Maisiuk, Yauhen (2014). Routing and fleet sizing for offshore supply vessels. In ., . (Eds.), ROUTE 2014 : International Workshop on Vehicle Routing, Intermodal Transport and Related Areas : June 1-4, 2014. Technical University of Denmark.
• Maisiuk, Yauhen & Gribkovskaia, Irina (2014). Strategic fleet sizing for offshore supply vessels with stochastic service time.
• Maisiuk, Yauhen & Gribkovskaia, Irina (2014). Modelling of supply vessel operations with simulation. Show summary

  Supply vessel schedules are generated according to service requirements of offshore installations characterized by cargo demand and weekly visit frequency. Stochastic factors such as weather uncertainty influence on the execution of schedules so that some visits are not performed. We consider several strategies how the cargo not delivered as planned may be shipped later. To compare the strategies and analyze their performance a discrete-event simulation model is developed. Tests on real data illustrate how application of these strategies for annual horizon reduces the number of delayed visits.

• Maisiuk, Yauhen & Gribkovskaia, Irina (2013). Fleet sizing for offshore supply vessels. Show summary

  Supply vessels provide offshore installations with necessary supplies on periodic basis from an onshore base according to weekly sailing plans. Each plan is built for a certain time horizon to guarantee required level of service to offshore installations at least cost. In a sailing plan several voyages are assigned to each vessel. The execution of sailing plans is affected by stochastic weather conditions. A vessel may not perform all visits within the planned voyage duration because of bad weather influencing vessel's sailing and service time. In such cases, additional vessels may be needed. Deciding on the number of supply vessels to hire on the long-term basis is an important part of the strategic fleet size planning. We present a discrete-event simulation model that evaluates alternative fleet size configurations of vessel fleet size for an annual time horizon. Keywords: Fleet Sizing, Routing, Simulation.

• Maisiuk, Yauhen & Gribkovskaia, Irina (2012). A simulation study of the fleet sizing problem for offshore supply vessels. Show summary

  The supply vessels provide offshore installations with supplies from an onshore base according to weekly sailing plans. The goal is to decide the cost-optimal fleet of vessels on the long-term hire. The problem is stochastic as sailing speed and service time depend on uncertain weather conditions. Due to delays some installations may not be served within the planned route duration, and not received supplies have to be delivered later. We propose a discrete-event simulation model which evaluates alternative fleet size configurations depending on several strategies of later delivery of supplies.

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