Ship speed optimization method combining Fisher optimal segmentation principle

An iterative optimization method that combines the principle of ordered clustering was proposed to address the strong correlation among route segmentation, weather loading, and ship speed optimization. Focusing on a single voyage task on a given route, the speed of an ocean-going container ship was...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Li, Xiaohe [verfasserIn] Sun, Baozhi [verfasserIn] Jin, Jianhai [verfasserIn] Ding, Jun [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Ordered clustering Route segmentation Weather loading Ship speed optimization Ship fuel-saving

Übergeordnetes Werk:	Enthalten in: Applied ocean research - Amsterdam [u.a.] : Elsevier Science, 1979, 140
Übergeordnetes Werk:	volume:140

DOI / URN:	10.1016/j.apor.2023.103743

Katalog-ID:	ELV065047052

Internformat


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245	1	0	\|a Ship speed optimization method combining Fisher optimal segmentation principle
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520			\|a An iterative optimization method that combines the principle of ordered clustering was proposed to address the strong correlation among route segmentation, weather loading, and ship speed optimization. Focusing on a single voyage task on a given route, the speed of an ocean-going container ship was optimized to achieve the minimum fuel consumption of the ship. The verified data-driven method was used to build a ship fuel consumption prediction model, and the Fisher optimal segmentation method was applied to segment ship routes. Subsequently, the speed optimization problem was solved using an iterative optimization method. The optimization results confirmed that the iterative optimization method has significant advantages in realizing route segmentation with the highest weather similarity within the segment. Extensive empirical studies on six case routes revealed the significant fuel-saving potential of the proposed iterative optimization method. Under different routes and weather conditions, the proposed iterative optimization method achieves a ship fuel-saving rate of 2.4 %–5.4 % and provides a reliable technical reference for the shipping industry to reduce the energy consumption and emissions of ships.
650		4	\|a Ordered clustering
650		4	\|a Route segmentation
650		4	\|a Weather loading
650		4	\|a Ship speed optimization
650		4	\|a Ship fuel-saving
700	1		\|a Sun, Baozhi \|e verfasserin \|4 aut
700	1		\|a Jin, Jianhai \|e verfasserin \|4 aut
700	1		\|a Ding, Jun \|e verfasserin \|4 aut
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952			\|d 140

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publishDate	2023
allfields	10.1016/j.apor.2023.103743 doi (DE-627)ELV065047052 (ELSEVIER)S0141-1187(23)00284-5 DE-627 ger DE-627 rda eng 550 570 VZ BIODIV DE-30 fid 38.90 bkl 50.92 bkl 56.30 bkl Li, Xiaohe verfasserin aut Ship speed optimization method combining Fisher optimal segmentation principle 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier An iterative optimization method that combines the principle of ordered clustering was proposed to address the strong correlation among route segmentation, weather loading, and ship speed optimization. Focusing on a single voyage task on a given route, the speed of an ocean-going container ship was optimized to achieve the minimum fuel consumption of the ship. The verified data-driven method was used to build a ship fuel consumption prediction model, and the Fisher optimal segmentation method was applied to segment ship routes. Subsequently, the speed optimization problem was solved using an iterative optimization method. The optimization results confirmed that the iterative optimization method has significant advantages in realizing route segmentation with the highest weather similarity within the segment. Extensive empirical studies on six case routes revealed the significant fuel-saving potential of the proposed iterative optimization method. Under different routes and weather conditions, the proposed iterative optimization method achieves a ship fuel-saving rate of 2.4 %–5.4 % and provides a reliable technical reference for the shipping industry to reduce the energy consumption and emissions of ships. Ordered clustering Route segmentation Weather loading Ship speed optimization Ship fuel-saving Sun, Baozhi verfasserin aut Jin, Jianhai verfasserin aut Ding, Jun verfasserin aut Enthalten in Applied ocean research Amsterdam [u.a.] : Elsevier Science, 1979 140 Online-Ressource (DE-627)306313944 (DE-600)1495994-X (DE-576)256144931 0141-1187 nnns volume:140 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.90 Ozeanologie Ozeanographie VZ 50.92 Meerestechnik VZ 56.30 Wasserbau VZ AR 140
spelling	10.1016/j.apor.2023.103743 doi (DE-627)ELV065047052 (ELSEVIER)S0141-1187(23)00284-5 DE-627 ger DE-627 rda eng 550 570 VZ BIODIV DE-30 fid 38.90 bkl 50.92 bkl 56.30 bkl Li, Xiaohe verfasserin aut Ship speed optimization method combining Fisher optimal segmentation principle 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier An iterative optimization method that combines the principle of ordered clustering was proposed to address the strong correlation among route segmentation, weather loading, and ship speed optimization. Focusing on a single voyage task on a given route, the speed of an ocean-going container ship was optimized to achieve the minimum fuel consumption of the ship. The verified data-driven method was used to build a ship fuel consumption prediction model, and the Fisher optimal segmentation method was applied to segment ship routes. Subsequently, the speed optimization problem was solved using an iterative optimization method. The optimization results confirmed that the iterative optimization method has significant advantages in realizing route segmentation with the highest weather similarity within the segment. Extensive empirical studies on six case routes revealed the significant fuel-saving potential of the proposed iterative optimization method. Under different routes and weather conditions, the proposed iterative optimization method achieves a ship fuel-saving rate of 2.4 %–5.4 % and provides a reliable technical reference for the shipping industry to reduce the energy consumption and emissions of ships. Ordered clustering Route segmentation Weather loading Ship speed optimization Ship fuel-saving Sun, Baozhi verfasserin aut Jin, Jianhai verfasserin aut Ding, Jun verfasserin aut Enthalten in Applied ocean research Amsterdam [u.a.] : Elsevier Science, 1979 140 Online-Ressource (DE-627)306313944 (DE-600)1495994-X (DE-576)256144931 0141-1187 nnns volume:140 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.90 Ozeanologie Ozeanographie VZ 50.92 Meerestechnik VZ 56.30 Wasserbau VZ AR 140
allfields_unstemmed	10.1016/j.apor.2023.103743 doi (DE-627)ELV065047052 (ELSEVIER)S0141-1187(23)00284-5 DE-627 ger DE-627 rda eng 550 570 VZ BIODIV DE-30 fid 38.90 bkl 50.92 bkl 56.30 bkl Li, Xiaohe verfasserin aut Ship speed optimization method combining Fisher optimal segmentation principle 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier An iterative optimization method that combines the principle of ordered clustering was proposed to address the strong correlation among route segmentation, weather loading, and ship speed optimization. Focusing on a single voyage task on a given route, the speed of an ocean-going container ship was optimized to achieve the minimum fuel consumption of the ship. The verified data-driven method was used to build a ship fuel consumption prediction model, and the Fisher optimal segmentation method was applied to segment ship routes. Subsequently, the speed optimization problem was solved using an iterative optimization method. The optimization results confirmed that the iterative optimization method has significant advantages in realizing route segmentation with the highest weather similarity within the segment. Extensive empirical studies on six case routes revealed the significant fuel-saving potential of the proposed iterative optimization method. Under different routes and weather conditions, the proposed iterative optimization method achieves a ship fuel-saving rate of 2.4 %–5.4 % and provides a reliable technical reference for the shipping industry to reduce the energy consumption and emissions of ships. Ordered clustering Route segmentation Weather loading Ship speed optimization Ship fuel-saving Sun, Baozhi verfasserin aut Jin, Jianhai verfasserin aut Ding, Jun verfasserin aut Enthalten in Applied ocean research Amsterdam [u.a.] : Elsevier Science, 1979 140 Online-Ressource (DE-627)306313944 (DE-600)1495994-X (DE-576)256144931 0141-1187 nnns volume:140 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.90 Ozeanologie Ozeanographie VZ 50.92 Meerestechnik VZ 56.30 Wasserbau VZ AR 140
allfieldsGer	10.1016/j.apor.2023.103743 doi (DE-627)ELV065047052 (ELSEVIER)S0141-1187(23)00284-5 DE-627 ger DE-627 rda eng 550 570 VZ BIODIV DE-30 fid 38.90 bkl 50.92 bkl 56.30 bkl Li, Xiaohe verfasserin aut Ship speed optimization method combining Fisher optimal segmentation principle 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier An iterative optimization method that combines the principle of ordered clustering was proposed to address the strong correlation among route segmentation, weather loading, and ship speed optimization. Focusing on a single voyage task on a given route, the speed of an ocean-going container ship was optimized to achieve the minimum fuel consumption of the ship. The verified data-driven method was used to build a ship fuel consumption prediction model, and the Fisher optimal segmentation method was applied to segment ship routes. Subsequently, the speed optimization problem was solved using an iterative optimization method. The optimization results confirmed that the iterative optimization method has significant advantages in realizing route segmentation with the highest weather similarity within the segment. Extensive empirical studies on six case routes revealed the significant fuel-saving potential of the proposed iterative optimization method. Under different routes and weather conditions, the proposed iterative optimization method achieves a ship fuel-saving rate of 2.4 %–5.4 % and provides a reliable technical reference for the shipping industry to reduce the energy consumption and emissions of ships. Ordered clustering Route segmentation Weather loading Ship speed optimization Ship fuel-saving Sun, Baozhi verfasserin aut Jin, Jianhai verfasserin aut Ding, Jun verfasserin aut Enthalten in Applied ocean research Amsterdam [u.a.] : Elsevier Science, 1979 140 Online-Ressource (DE-627)306313944 (DE-600)1495994-X (DE-576)256144931 0141-1187 nnns volume:140 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.90 Ozeanologie Ozeanographie VZ 50.92 Meerestechnik VZ 56.30 Wasserbau VZ AR 140
allfieldsSound	10.1016/j.apor.2023.103743 doi (DE-627)ELV065047052 (ELSEVIER)S0141-1187(23)00284-5 DE-627 ger DE-627 rda eng 550 570 VZ BIODIV DE-30 fid 38.90 bkl 50.92 bkl 56.30 bkl Li, Xiaohe verfasserin aut Ship speed optimization method combining Fisher optimal segmentation principle 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier An iterative optimization method that combines the principle of ordered clustering was proposed to address the strong correlation among route segmentation, weather loading, and ship speed optimization. Focusing on a single voyage task on a given route, the speed of an ocean-going container ship was optimized to achieve the minimum fuel consumption of the ship. The verified data-driven method was used to build a ship fuel consumption prediction model, and the Fisher optimal segmentation method was applied to segment ship routes. Subsequently, the speed optimization problem was solved using an iterative optimization method. The optimization results confirmed that the iterative optimization method has significant advantages in realizing route segmentation with the highest weather similarity within the segment. Extensive empirical studies on six case routes revealed the significant fuel-saving potential of the proposed iterative optimization method. Under different routes and weather conditions, the proposed iterative optimization method achieves a ship fuel-saving rate of 2.4 %–5.4 % and provides a reliable technical reference for the shipping industry to reduce the energy consumption and emissions of ships. Ordered clustering Route segmentation Weather loading Ship speed optimization Ship fuel-saving Sun, Baozhi verfasserin aut Jin, Jianhai verfasserin aut Ding, Jun verfasserin aut Enthalten in Applied ocean research Amsterdam [u.a.] : Elsevier Science, 1979 140 Online-Ressource (DE-627)306313944 (DE-600)1495994-X (DE-576)256144931 0141-1187 nnns volume:140 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.90 Ozeanologie Ozeanographie VZ 50.92 Meerestechnik VZ 56.30 Wasserbau VZ AR 140
language	English
source	Enthalten in Applied ocean research 140 volume:140
sourceStr	Enthalten in Applied ocean research 140 volume:140
format_phy_str_mv	Article
bklname	Ozeanologie Ozeanographie Meerestechnik Wasserbau
institution	findex.gbv.de
topic_facet	Ordered clustering Route segmentation Weather loading Ship speed optimization Ship fuel-saving
dewey-raw	550
isfreeaccess_bool	false
container_title	Applied ocean research
authorswithroles_txt_mv	Li, Xiaohe @@aut@@ Sun, Baozhi @@aut@@ Jin, Jianhai @@aut@@ Ding, Jun @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	306313944
dewey-sort	3550
id	ELV065047052
language_de	englisch
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author	Li, Xiaohe
spellingShingle	Li, Xiaohe ddc 550 fid BIODIV bkl 38.90 bkl 50.92 bkl 56.30 misc Ordered clustering misc Route segmentation misc Weather loading misc Ship speed optimization misc Ship fuel-saving Ship speed optimization method combining Fisher optimal segmentation principle
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title	Ship speed optimization method combining Fisher optimal segmentation principle
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title_full	Ship speed optimization method combining Fisher optimal segmentation principle
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title_sort	ship speed optimization method combining fisher optimal segmentation principle
title_auth	Ship speed optimization method combining Fisher optimal segmentation principle
abstract	An iterative optimization method that combines the principle of ordered clustering was proposed to address the strong correlation among route segmentation, weather loading, and ship speed optimization. Focusing on a single voyage task on a given route, the speed of an ocean-going container ship was optimized to achieve the minimum fuel consumption of the ship. The verified data-driven method was used to build a ship fuel consumption prediction model, and the Fisher optimal segmentation method was applied to segment ship routes. Subsequently, the speed optimization problem was solved using an iterative optimization method. The optimization results confirmed that the iterative optimization method has significant advantages in realizing route segmentation with the highest weather similarity within the segment. Extensive empirical studies on six case routes revealed the significant fuel-saving potential of the proposed iterative optimization method. Under different routes and weather conditions, the proposed iterative optimization method achieves a ship fuel-saving rate of 2.4 %–5.4 % and provides a reliable technical reference for the shipping industry to reduce the energy consumption and emissions of ships.
abstractGer	An iterative optimization method that combines the principle of ordered clustering was proposed to address the strong correlation among route segmentation, weather loading, and ship speed optimization. Focusing on a single voyage task on a given route, the speed of an ocean-going container ship was optimized to achieve the minimum fuel consumption of the ship. The verified data-driven method was used to build a ship fuel consumption prediction model, and the Fisher optimal segmentation method was applied to segment ship routes. Subsequently, the speed optimization problem was solved using an iterative optimization method. The optimization results confirmed that the iterative optimization method has significant advantages in realizing route segmentation with the highest weather similarity within the segment. Extensive empirical studies on six case routes revealed the significant fuel-saving potential of the proposed iterative optimization method. Under different routes and weather conditions, the proposed iterative optimization method achieves a ship fuel-saving rate of 2.4 %–5.4 % and provides a reliable technical reference for the shipping industry to reduce the energy consumption and emissions of ships.
abstract_unstemmed	An iterative optimization method that combines the principle of ordered clustering was proposed to address the strong correlation among route segmentation, weather loading, and ship speed optimization. Focusing on a single voyage task on a given route, the speed of an ocean-going container ship was optimized to achieve the minimum fuel consumption of the ship. The verified data-driven method was used to build a ship fuel consumption prediction model, and the Fisher optimal segmentation method was applied to segment ship routes. Subsequently, the speed optimization problem was solved using an iterative optimization method. The optimization results confirmed that the iterative optimization method has significant advantages in realizing route segmentation with the highest weather similarity within the segment. Extensive empirical studies on six case routes revealed the significant fuel-saving potential of the proposed iterative optimization method. Under different routes and weather conditions, the proposed iterative optimization method achieves a ship fuel-saving rate of 2.4 %–5.4 % and provides a reliable technical reference for the shipping industry to reduce the energy consumption and emissions of ships.
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title_short	Ship speed optimization method combining Fisher optimal segmentation principle
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Ship speed optimization method combining Fisher optimal segmentation principle

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