Weak and strong convergence of a modified double inertial projection algorithm for solving variational inequality problems

We propose a new double inertial projection algorithm by combining the subgradient extragradient algorithm with the projection contraction algorithm. On one hand, our algorithm requires the mapping to be Lipschitz continuous, but without the Lipschitz constant. On the other hand, this algorithm only...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Zhang, Huan [verfasserIn] Liu, Xiaolan [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Double inertial Variational inequality Weak convergence Strong convergence

Übergeordnetes Werk:	Enthalten in: No title available - 130
Übergeordnetes Werk:	volume:130

DOI / URN:	10.1016/j.cnsns.2023.107766

Katalog-ID:	ELV066581141

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245	1	0	\|a Weak and strong convergence of a modified double inertial projection algorithm for solving variational inequality problems
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520			\|a We propose a new double inertial projection algorithm by combining the subgradient extragradient algorithm with the projection contraction algorithm. On one hand, our algorithm requires the mapping to be Lipschitz continuous, but without the Lipschitz constant. On the other hand, this algorithm only requires the mapping is quasimonotone.Under some mild conditions, we obtain a weak convergence result of the algorithm. In addition, we give a strong convergence result of the algorithm when the mapping is strongly pseudomonotone. Some numerical experiments are given to show the effectiveness of the proposed algorithm.
650		4	\|a Double inertial
650		4	\|a Variational inequality
650		4	\|a Weak convergence
650		4	\|a Strong convergence
700	1		\|a Liu, Xiaolan \|e verfasserin \|0 (orcid)0000-0001-8904-6782 \|4 aut
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publishDate	2023
allfields	10.1016/j.cnsns.2023.107766 doi (DE-627)ELV066581141 (ELSEVIER)S1007-5704(23)00687-1 DE-627 ger DE-627 rda eng Zhang, Huan verfasserin aut Weak and strong convergence of a modified double inertial projection algorithm for solving variational inequality problems 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier We propose a new double inertial projection algorithm by combining the subgradient extragradient algorithm with the projection contraction algorithm. On one hand, our algorithm requires the mapping to be Lipschitz continuous, but without the Lipschitz constant. On the other hand, this algorithm only requires the mapping is quasimonotone.Under some mild conditions, we obtain a weak convergence result of the algorithm. In addition, we give a strong convergence result of the algorithm when the mapping is strongly pseudomonotone. Some numerical experiments are given to show the effectiveness of the proposed algorithm. Double inertial Variational inequality Weak convergence Strong convergence Liu, Xiaolan verfasserin (orcid)0000-0001-8904-6782 aut Enthalten in No title available 130 (DE-627)352827580 1007-5704 nnns volume:130 GBV_USEFLAG_U GBV_ELV SYSFLAG_U 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_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_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_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_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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 130
spelling	10.1016/j.cnsns.2023.107766 doi (DE-627)ELV066581141 (ELSEVIER)S1007-5704(23)00687-1 DE-627 ger DE-627 rda eng Zhang, Huan verfasserin aut Weak and strong convergence of a modified double inertial projection algorithm for solving variational inequality problems 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier We propose a new double inertial projection algorithm by combining the subgradient extragradient algorithm with the projection contraction algorithm. On one hand, our algorithm requires the mapping to be Lipschitz continuous, but without the Lipschitz constant. On the other hand, this algorithm only requires the mapping is quasimonotone.Under some mild conditions, we obtain a weak convergence result of the algorithm. In addition, we give a strong convergence result of the algorithm when the mapping is strongly pseudomonotone. Some numerical experiments are given to show the effectiveness of the proposed algorithm. Double inertial Variational inequality Weak convergence Strong convergence Liu, Xiaolan verfasserin (orcid)0000-0001-8904-6782 aut Enthalten in No title available 130 (DE-627)352827580 1007-5704 nnns volume:130 GBV_USEFLAG_U GBV_ELV SYSFLAG_U 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_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_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_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_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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 130
allfields_unstemmed	10.1016/j.cnsns.2023.107766 doi (DE-627)ELV066581141 (ELSEVIER)S1007-5704(23)00687-1 DE-627 ger DE-627 rda eng Zhang, Huan verfasserin aut Weak and strong convergence of a modified double inertial projection algorithm for solving variational inequality problems 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier We propose a new double inertial projection algorithm by combining the subgradient extragradient algorithm with the projection contraction algorithm. On one hand, our algorithm requires the mapping to be Lipschitz continuous, but without the Lipschitz constant. On the other hand, this algorithm only requires the mapping is quasimonotone.Under some mild conditions, we obtain a weak convergence result of the algorithm. In addition, we give a strong convergence result of the algorithm when the mapping is strongly pseudomonotone. Some numerical experiments are given to show the effectiveness of the proposed algorithm. Double inertial Variational inequality Weak convergence Strong convergence Liu, Xiaolan verfasserin (orcid)0000-0001-8904-6782 aut Enthalten in No title available 130 (DE-627)352827580 1007-5704 nnns volume:130 GBV_USEFLAG_U GBV_ELV SYSFLAG_U 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_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_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_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_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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 130
allfieldsGer	10.1016/j.cnsns.2023.107766 doi (DE-627)ELV066581141 (ELSEVIER)S1007-5704(23)00687-1 DE-627 ger DE-627 rda eng Zhang, Huan verfasserin aut Weak and strong convergence of a modified double inertial projection algorithm for solving variational inequality problems 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier We propose a new double inertial projection algorithm by combining the subgradient extragradient algorithm with the projection contraction algorithm. On one hand, our algorithm requires the mapping to be Lipschitz continuous, but without the Lipschitz constant. On the other hand, this algorithm only requires the mapping is quasimonotone.Under some mild conditions, we obtain a weak convergence result of the algorithm. In addition, we give a strong convergence result of the algorithm when the mapping is strongly pseudomonotone. Some numerical experiments are given to show the effectiveness of the proposed algorithm. Double inertial Variational inequality Weak convergence Strong convergence Liu, Xiaolan verfasserin (orcid)0000-0001-8904-6782 aut Enthalten in No title available 130 (DE-627)352827580 1007-5704 nnns volume:130 GBV_USEFLAG_U GBV_ELV SYSFLAG_U 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_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_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_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_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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 130
allfieldsSound	10.1016/j.cnsns.2023.107766 doi (DE-627)ELV066581141 (ELSEVIER)S1007-5704(23)00687-1 DE-627 ger DE-627 rda eng Zhang, Huan verfasserin aut Weak and strong convergence of a modified double inertial projection algorithm for solving variational inequality problems 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier We propose a new double inertial projection algorithm by combining the subgradient extragradient algorithm with the projection contraction algorithm. On one hand, our algorithm requires the mapping to be Lipschitz continuous, but without the Lipschitz constant. On the other hand, this algorithm only requires the mapping is quasimonotone.Under some mild conditions, we obtain a weak convergence result of the algorithm. In addition, we give a strong convergence result of the algorithm when the mapping is strongly pseudomonotone. Some numerical experiments are given to show the effectiveness of the proposed algorithm. Double inertial Variational inequality Weak convergence Strong convergence Liu, Xiaolan verfasserin (orcid)0000-0001-8904-6782 aut Enthalten in No title available 130 (DE-627)352827580 1007-5704 nnns volume:130 GBV_USEFLAG_U GBV_ELV SYSFLAG_U 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_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_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_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_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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 130
language	English
source	Enthalten in No title available 130 volume:130
sourceStr	Enthalten in No title available 130 volume:130
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Double inertial Variational inequality Weak convergence Strong convergence
isfreeaccess_bool	false
container_title	No title available
authorswithroles_txt_mv	Zhang, Huan @@aut@@ Liu, Xiaolan @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	352827580
id	ELV066581141
language_de	englisch
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author	Zhang, Huan
spellingShingle	Zhang, Huan misc Double inertial misc Variational inequality misc Weak convergence misc Strong convergence Weak and strong convergence of a modified double inertial projection algorithm for solving variational inequality problems
authorStr	Zhang, Huan
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topic_title	Weak and strong convergence of a modified double inertial projection algorithm for solving variational inequality problems Double inertial Variational inequality Weak convergence Strong convergence
topic	misc Double inertial misc Variational inequality misc Weak convergence misc Strong convergence
topic_unstemmed	misc Double inertial misc Variational inequality misc Weak convergence misc Strong convergence
topic_browse	misc Double inertial misc Variational inequality misc Weak convergence misc Strong convergence
format_facet	Elektronische Aufsätze Aufsätze Elektronische Ressource
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title	Weak and strong convergence of a modified double inertial projection algorithm for solving variational inequality problems
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title_full	Weak and strong convergence of a modified double inertial projection algorithm for solving variational inequality problems
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title_sort	weak and strong convergence of a modified double inertial projection algorithm for solving variational inequality problems
title_auth	Weak and strong convergence of a modified double inertial projection algorithm for solving variational inequality problems
abstract	We propose a new double inertial projection algorithm by combining the subgradient extragradient algorithm with the projection contraction algorithm. On one hand, our algorithm requires the mapping to be Lipschitz continuous, but without the Lipschitz constant. On the other hand, this algorithm only requires the mapping is quasimonotone.Under some mild conditions, we obtain a weak convergence result of the algorithm. In addition, we give a strong convergence result of the algorithm when the mapping is strongly pseudomonotone. Some numerical experiments are given to show the effectiveness of the proposed algorithm.
abstractGer	We propose a new double inertial projection algorithm by combining the subgradient extragradient algorithm with the projection contraction algorithm. On one hand, our algorithm requires the mapping to be Lipschitz continuous, but without the Lipschitz constant. On the other hand, this algorithm only requires the mapping is quasimonotone.Under some mild conditions, we obtain a weak convergence result of the algorithm. In addition, we give a strong convergence result of the algorithm when the mapping is strongly pseudomonotone. Some numerical experiments are given to show the effectiveness of the proposed algorithm.
abstract_unstemmed	We propose a new double inertial projection algorithm by combining the subgradient extragradient algorithm with the projection contraction algorithm. On one hand, our algorithm requires the mapping to be Lipschitz continuous, but without the Lipschitz constant. On the other hand, this algorithm only requires the mapping is quasimonotone.Under some mild conditions, we obtain a weak convergence result of the algorithm. In addition, we give a strong convergence result of the algorithm when the mapping is strongly pseudomonotone. Some numerical experiments are given to show the effectiveness of the proposed algorithm.
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title_short	Weak and strong convergence of a modified double inertial projection algorithm for solving variational inequality problems
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author2	Liu, Xiaolan
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doi_str	10.1016/j.cnsns.2023.107766
up_date	2024-07-06T18:15:56.828Z
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Weak and strong convergence of a modified double inertial projection algorithm for solving variational inequality problems

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