A framework for multi-objective optimization of Arctic offshore support vessels

An Arctic vessel operates in a fragile Arctic environment that requires analyzing an eco-efficiency besides cost-efficiency in the conceptual design – phase that mainly determines a ship's performance. We present a software framework to optimize Arctic offshore support vessels for Cost- and Eco...

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Bibliographic Details
Main Authors: Kondratenko, Aleksandr, Kujala, Pentti
Other Authors: Department of Mechanical Engineering, Marine Technology, Aalto-yliopisto, Aalto University
Format: Other/Unknown Material
Language:English
Published: POAC 2021
Subjects:
Ship design
Offshore
Arctic
Multi-objective optimization
Artificial Bee Colony algorithm
Online Access:https://aaltodoc.aalto.fi/handle/123456789/111641
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spelling ftaaltouniv:oai:aaltodoc.aalto.fi:123456789/111641 2023-05-15T14:21:57+02:00 A framework for multi-objective optimization of Arctic offshore support vessels Kondratenko, Aleksandr Kujala, Pentti Department of Mechanical Engineering Marine Technology Aalto-yliopisto Aalto University 2021-06-30 application/pdf https://aaltodoc.aalto.fi/handle/123456789/111641 en eng POAC Proceedings of the 26th International Conference on Port and Ocean Engineering under Arctic Conditions POAC 2021 Proceedings of the International Conference on Port and Ocean Engineering under Arctic Conditions Kondratenko , A & Kujala , P 2021 , A framework for multi-objective optimization of Arctic offshore support vessels . in Proceedings of the 26th International Conference on Port and Ocean Engineering under Arctic Conditions POAC 2021 . Proceedings of the International Conference on Port and Ocean Engineering under Arctic Conditions , Luleå University of Technology , International Conference on Port and Ocean Engineering under Arctic Conditions , Moscow , Russian Federation , 14/06/2021 . < https://www.poac.com/Papers/2021/pdf/POAC21-089.pdf > 0376-6756 2077-7841 PURE UUID: c4f9afd2-456a-4824-afd6-393fc5109972 PURE ITEMURL: https://research.aalto.fi/en/publications/c4f9afd2-456a-4824-afd6-393fc5109972 PURE LINK: https://www.poac.com/Papers/2021/pdf/POAC21-089.pdf PURE FILEURL: https://research.aalto.fi/files/76625359/POAC21_089.pdf https://aaltodoc.aalto.fi/handle/123456789/111641 URN:NBN:fi:aalto-2021121510782 openAccess Ship design Offshore Arctic Multi-objective optimization Artificial Bee Colony algorithm A4 Artikkeli konferenssijulkaisussa publishedVersion 2021 ftaaltouniv 2023-02-01T23:57:53Z An Arctic vessel operates in a fragile Arctic environment that requires analyzing an eco-efficiency besides cost-efficiency in the conceptual design – phase that mainly determines a ship's performance. We present a software framework to optimize Arctic offshore support vessels for Cost- and Eco-efficiency using the Artificial Bee Colony algorithm. The framework scans the feasible design space to find a Pareto front, considering essential ship qualities in a specific operational context. The object-oriented structure of the program modules makes them independently reusable for a wide range of applications. Peer reviewed Other/Unknown Material Arctic Arctic Aalto University Publication Archive (Aaltodoc) Arctic
institution Open Polar
collection Aalto University Publication Archive (Aaltodoc)
op_collection_id ftaaltouniv
language English
topic Ship design
Offshore
Arctic
Multi-objective optimization
Artificial Bee Colony algorithm
spellingShingle Ship design
Offshore
Arctic
Multi-objective optimization
Artificial Bee Colony algorithm
Kondratenko, Aleksandr
Kujala, Pentti
A framework for multi-objective optimization of Arctic offshore support vessels
topic_facet Ship design
Offshore
Arctic
Multi-objective optimization
Artificial Bee Colony algorithm
description An Arctic vessel operates in a fragile Arctic environment that requires analyzing an eco-efficiency besides cost-efficiency in the conceptual design – phase that mainly determines a ship's performance. We present a software framework to optimize Arctic offshore support vessels for Cost- and Eco-efficiency using the Artificial Bee Colony algorithm. The framework scans the feasible design space to find a Pareto front, considering essential ship qualities in a specific operational context. The object-oriented structure of the program modules makes them independently reusable for a wide range of applications. Peer reviewed
author2 Department of Mechanical Engineering
Marine Technology
Aalto-yliopisto
Aalto University
format Other/Unknown Material
author Kondratenko, Aleksandr
Kujala, Pentti
author_facet Kondratenko, Aleksandr
Kujala, Pentti
author_sort Kondratenko, Aleksandr
title A framework for multi-objective optimization of Arctic offshore support vessels
title_short A framework for multi-objective optimization of Arctic offshore support vessels
title_full A framework for multi-objective optimization of Arctic offshore support vessels
title_fullStr A framework for multi-objective optimization of Arctic offshore support vessels
title_full_unstemmed A framework for multi-objective optimization of Arctic offshore support vessels
title_sort framework for multi-objective optimization of arctic offshore support vessels
publisher POAC
publishDate 2021
url https://aaltodoc.aalto.fi/handle/123456789/111641
geographic Arctic
geographic_facet Arctic
genre Arctic
Arctic
genre_facet Arctic
Arctic
op_relation Proceedings of the 26th International Conference on Port and Ocean Engineering under Arctic Conditions POAC 2021
Proceedings of the International Conference on Port and Ocean Engineering under Arctic Conditions
Kondratenko , A & Kujala , P 2021 , A framework for multi-objective optimization of Arctic offshore support vessels . in Proceedings of the 26th International Conference on Port and Ocean Engineering under Arctic Conditions POAC 2021 . Proceedings of the International Conference on Port and Ocean Engineering under Arctic Conditions , Luleå University of Technology , International Conference on Port and Ocean Engineering under Arctic Conditions , Moscow , Russian Federation , 14/06/2021 . < https://www.poac.com/Papers/2021/pdf/POAC21-089.pdf >
0376-6756
2077-7841
PURE UUID: c4f9afd2-456a-4824-afd6-393fc5109972
PURE ITEMURL: https://research.aalto.fi/en/publications/c4f9afd2-456a-4824-afd6-393fc5109972
PURE LINK: https://www.poac.com/Papers/2021/pdf/POAC21-089.pdf
PURE FILEURL: https://research.aalto.fi/files/76625359/POAC21_089.pdf
https://aaltodoc.aalto.fi/handle/123456789/111641
URN:NBN:fi:aalto-2021121510782
op_rights openAccess
_version_ 1766294640428843008

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