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THE CONCEPT OF AN INTEGRATED INFORMATION SYSTEM FOR PLANNING OF FLEET OPERATION IN THE ARCTICJOURNAL: 2019, ¹1(33), p. 129-143
RUBRIC: Problems of the Northern Sea Route
AUTHORS: Timofeyev O.Y., Tarovik O.V., Topaj A.G., Mironov Y.U., Frolov S.V., Buyanov A.S., Gorbachev M.A., Bengert A.A.
ORGANIZATIONS: Krylov State Research Centre, State Research Center "Arctic and Antarctic Research Institute", Central Marine Research and Design Institute, Scientific Logistics Center LLC, Northern Sea Route Directorate of the State Atomiñ Energy Corporation Rosatom
The article was received on: 24.12.2018
Keywords: Arctic fleet, ice routing, icebreaker, machine learning, planning of fleet operation, scheduling, ice-going vessels, ship on-board recorder, planning levels, economic efficiency of shipping
Bibliographic description: Timofeyev O.Y., Tarovik O.V., Topaj A.G., Mironov Y.U., Frolov S.V., Buyanov A.S., Gorbachev M.A., Bengert A.A. The concept of an integrated information system for planning of fleet operation in the Arctic. Arctic: ecology and economy, 2019, no. 1(33), pp. 129-143. DOI: 10.25283/2223-4594-2019-1-129-143. (In Russian).
There are several reasons for the multiple increase in intensity of Arctic shipping in the near future. This makes quite relevant the development of tools and algorithms for information support of navigation in this complex region.In this article, we describe the concept of an integrated information system for planning the operation of cargo ships and icebreakers in the Arctic. The planning task is divided into three levels: operational, tactical and strategic. The goal of operational-tactical planning is to increase the efficiency of the maritime transport system, taking into account the requirements for ice navigation safety. This task includes both the optimization of vessel routes and the development of an optimal plan for their icebreaking support throughout the region. Such a plan includes geographic points and dates for the convoy formation and splitting up, as well as the convoy composition, recommended routes in ice, etc.
The structure of the Centralized system for tactical and operational planning of shipping in the Arctic includes four main domains. The “Ships” Domain includes the software infrastructure for the generation and storage of information models of vessels, icebreakers, as well as computational models of vessel movement in ice. The “Passages” Domain is used to store data on scheduled, current and completed passages of ships and icebreakers. The “Nature” Domain describes and displays the environmental parameters. It contains both the static information elements (navigation maps and databases of navigation conditions) and the components for operational monitoring and forecasting of weather and ice cover dynamics. The ship onboard recorders of voyage data and environmental parameters play a special role in the System, since they allow collecting big data to improve various computationalalgorithms. The services joined in the “Planning” Domain from the intellectual core of the System; they are related to the methods of automatic decision making andtheir implementation is possible with the use of modern technologies, such as knowledge bases and machine learning techniques.
The article highlights the main groups of scientific and methodological problems that challenges the implementationof the proposed System. They are: (1) spatial logistic planning of ships’ and icebreakers’ operation at the tactical and operational levels; (2) the need to improve the accuracy as well asthe horizon of operational ice forecasts; (3) the development of a robust computational model to predict the parameters of vessel and convoy movement in ice, taking into account all ice features that determine ship performance.Implementationof the System will improve the economic efficiency and safety of Arctic shipping by means of the centralized planning of ships and icebreakersoperation.
1. Vauraste T. Icepool — Holistic use of global icebreaker fleet. Maritime cluster in the Baltic Sea region and beyond. [S. l.], 2016, P. 104—105.
2. International Code for Ships Operating in Polar Waters. Guidance on Methodology for assessing operational capabilities and limitations in ice. Polar Operational Limit assessment Risk Indexing System (POLARIS). [S. l.], 6 June 2016. MSC.1/Circ.1519.
3. Christiansen M., Fagerholt K., Nygreen B., Ronen D.Maritime Transportation. Handbooks in Operations Research and Management Science. C. Barnhart, G. Laporte (eds.). North Holland, Amsterdam, 2007, pp. 189—284.
4. Bakharev A. A., Kosorotov A. V., Krest’yantsev A. B.,Tarovik O. V., Topazh A. G. Ierarkhiya urovnei prinyatiya reshenii v imitatsionnom modelirovanii morskikh perevozok. [The hierarchy of decision levels in the computer simulation of maritime transportation]. Tr. konf. IMMOD-2015. Vol. 1. Moscow, IPU RAN, 2015, pp. 34—39. (In Russian).
5. Tarovik O. V., Topazh A. G., Krest’yantsev A. B., KondratenkoA. A. Modelirovanie sistem arkticheskogo morskogo transporta: osnovy mezhdistsiplinarnogo podkhoda i opyt prakticheskikh rabot. [Arctic Marine Transport System Simulation: Multidisciplinary Approach Fundamentals and Practical Experience]. Arktika: ekologiya i ekonomika, 2017, no. 1 (25), pp. 86—101. (In Russian).
6. Frolov S. V. Vliyanie orientatsii narushenii sploshnosti l’da na effektivnost’ dvizheniya sudov v arkticheskom basseine v letnii period. [The influence of orientation of ice leads on the efficiency of vessel navigation in the Arctic in summer period]. Problemy Arktiki i A ntarktiki, 2013, no. 3 (97), pp. 35—45. (In Russian).
7. Adamovich N. M., Buzuyev A. Ya., Fedyakov V. E. The empiric model of vessel movement in the ice and eneralization of the experience of the model usage in hydrometeorological support of shipping in the Arctic. Proceedings of POAC-1995. Vol. 2. Murmansk, 1995, pp. 30—40.
8. Brovin A. I., Klyachkin S. V., Bhat S. U. Application of an empirical-statistical model of ship motion in ice to new types of icebreakers and ships. Proceedings of OMAE-1997. Vol. 4. Yokohama, Japan, 1997, pp. 43—49.
9. Montewka J., Sinclair H., Kujala P., Haapala J., LensuM. Modelling ship performance in ice using Bayesian Networks. Proceedings of POAC-2013. spoo, Finland, 2013, 12 p.
10. Bushuev A. V., Volkov N. A., Gudkovich Z. M., NovikovYu. R., Prokof’ev V. A. Avtomatizirovannaya ledovo-informatsionnaya sistema dlya Arktiki (ALISA). [Automated Ice Information System for the Arctic]. Tr. AANII, 1977, vol. 343, pp. 29—47. (In Russian).
11. Mironov E. U., Ashik I. M., Brestkin S. V., Smirnov V. G.Adaptiruemyi kompleks monitoringa i prognozirovaniya sostoyaniya atmosfery i gidrosfery. [Adaptable complex for monitoring and forecasting the state of the atmosphere and hydrosphere]. Problemy Arktiki I Antarktiki, 2009, no. 3 (83), pp. 88—97. (In Russian).
12. Tarovik O. V., Topazh A. G., Krest’yantsev A. B., KondratenkoA. A., Zaikin D. A. Kompleksnaya imitatsionnaya model’ morskoi transportno-tekhnologicheskoi sistemy platformy “Prirazlomnaya”. [Comprehensive Simulation Model of Marine Transport and Support System for “Prirazlomnaya” Platform]. Arktika: ekologiya i ekonomika, 2017, no. 3 (27), pp. 86—103. (In Russian).
13. Rybii V. V., Kazunin D. V., Timofeev O. Ya., BelyashovV. A., Pronyashkin A. A., Kazunin I. D. Rossiiskaya ledovaya informatsionnaya sistema (LIS) — zalog uspeshnogo osvoeniya Arktiki. [Russian Ice Information System (LIS) — the key to successful development of the Arctic]. Mor. vestn, 2016, no. 4 (60), pp. 63—67. (In Russian).
14. Frolov S. V., Klein A. E., Tret’yakov V. Yu. Rezul’taty ispol’zovaniya tsifrovogo televizionnogo kompleksa dlya izmerenii tolshchiny l’da v Arkticheskom basseine v 2004—2005 gg. [The results of using a digital television complex for measuring ice thickness in the Arctic basin in 2004—2005]. Problemy Arktiki i Antarktiki, 2007, no. 1 (75), pp. 123—127. (In Russian).
15. Tret’yakov V. Yu., Frolov S. V., Klein A. E. Metodika rascheta skorosti slozheniya kanala v ledyanom pokrove po dannym televizionnykh snimkov. [The method to calculate the rate of closing of channel in ice cover based on television imagery data]. Meteor. vestn., 2010, no. 2 (7), pp. 12—29. (In Russian).
16. Pronyashkin A. A., Karulin E. B., Kazantsev M. A. Ledovaya informatsionnaya sistema dlya Arkticheskogo shel’fa. [Ice information system for the Arctic shelf]. Tr. Mezhdunar. konf. Offshore Marintec Russia-2018. 2—5 oktyabrya 2018 g. St. Petersburg, 2018. (In Russian).
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