An improved relaxed inertial projection algorithm for solving the minimum-norm solution of variational inequality and fixed point problems

Abstract In this paper, a modified projection algorithm is proposed in order to solve a common element of the solution set of monotone variational inequality and the fixed point set of a class of quasi-pseudo-contractive mapping. This algorithm requires the monotonicity and Lipschitz continuity of t...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Zhang, Huan [verfasserIn] Liu, Xiaolan Deng, Jia Sun, Yan

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Quasi-pseudo-contractive mapping Variational inequality Monotonicity Fixed point

Anmerkung:	© The Author(s) under exclusive licence to Korean Society for Informatics and Computational Applied Mathematics 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Übergeordnetes Werk:	Enthalten in: Journal of applied mathematics and computing - Berlin : Springer, 2006, 69(2023), 3 vom: 03. Apr., Seite 2717-2739
Übergeordnetes Werk:	volume:69 ; year:2023 ; number:3 ; day:03 ; month:04 ; pages:2717-2739

Links:	Volltext

DOI / URN:	10.1007/s12190-023-01853-z

Katalog-ID:	SPR051657066

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245	1	3	\|a An improved relaxed inertial projection algorithm for solving the minimum-norm solution of variational inequality and fixed point problems
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520			\|a Abstract In this paper, a modified projection algorithm is proposed in order to solve a common element of the solution set of monotone variational inequality and the fixed point set of a class of quasi-pseudo-contractive mapping. This algorithm requires the monotonicity and Lipschitz continuity of the mapping, but don’t need to know Lipschitz constant. On one hand, this algorithm does not compute the projection onto the feasible set at each iteration, on the other hand, the strong convergence of the sequence generated by the algorithm can be obtained without viscosity technology, and the convergence rate of the algorithm better than some algorithms, and the effect of the algorithm is illustrated by two numerical experiments.
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912			\|a GBV_ILN_105
912			\|a GBV_ILN_110
912			\|a GBV_ILN_120
912			\|a GBV_ILN_138
912			\|a GBV_ILN_150
912			\|a GBV_ILN_151
912			\|a GBV_ILN_152
912			\|a GBV_ILN_161
912			\|a GBV_ILN_165
912			\|a GBV_ILN_170
912			\|a GBV_ILN_171
912			\|a GBV_ILN_187
912			\|a GBV_ILN_213
912			\|a GBV_ILN_224
912			\|a GBV_ILN_230
912			\|a GBV_ILN_250
912			\|a GBV_ILN_281
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_636
912			\|a GBV_ILN_702
912			\|a GBV_ILN_2001
912			\|a GBV_ILN_2003
912			\|a GBV_ILN_2004
912			\|a GBV_ILN_2005
912			\|a GBV_ILN_2006
912			\|a GBV_ILN_2007
912			\|a GBV_ILN_2008
912			\|a GBV_ILN_2009
912			\|a GBV_ILN_2010
912			\|a GBV_ILN_2011
912			\|a GBV_ILN_2014
912			\|a GBV_ILN_2015
912			\|a GBV_ILN_2020
912			\|a GBV_ILN_2021
912			\|a GBV_ILN_2025
912			\|a GBV_ILN_2026
912			\|a GBV_ILN_2027
912			\|a GBV_ILN_2031
912			\|a GBV_ILN_2034
912			\|a GBV_ILN_2037
912			\|a GBV_ILN_2038
912			\|a GBV_ILN_2039
912			\|a GBV_ILN_2044
912			\|a GBV_ILN_2048
912			\|a GBV_ILN_2049
912			\|a GBV_ILN_2050
912			\|a GBV_ILN_2055
912			\|a GBV_ILN_2056
912			\|a GBV_ILN_2057
912			\|a GBV_ILN_2059
912			\|a GBV_ILN_2061
912			\|a GBV_ILN_2064
912			\|a GBV_ILN_2065
912			\|a GBV_ILN_2068
912			\|a GBV_ILN_2088
912			\|a GBV_ILN_2093
912			\|a GBV_ILN_2106
912			\|a GBV_ILN_2107
912			\|a GBV_ILN_2110
912			\|a GBV_ILN_2111
912			\|a GBV_ILN_2112
912			\|a GBV_ILN_2113
912			\|a GBV_ILN_2118
912			\|a GBV_ILN_2122
912			\|a GBV_ILN_2129
912			\|a GBV_ILN_2143
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912			\|a GBV_ILN_2336
912			\|a GBV_ILN_2446
912			\|a GBV_ILN_2470
912			\|a GBV_ILN_2507
912			\|a GBV_ILN_2522
912			\|a GBV_ILN_2548
912			\|a GBV_ILN_4035
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912			\|a GBV_ILN_4333
912			\|a GBV_ILN_4334
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allfields	10.1007/s12190-023-01853-z doi (DE-627)SPR051657066 (SPR)s12190-023-01853-z-e DE-627 ger DE-627 rakwb eng Zhang, Huan verfasserin aut An improved relaxed inertial projection algorithm for solving the minimum-norm solution of variational inequality and fixed point problems 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) under exclusive licence to Korean Society for Informatics and Computational Applied Mathematics 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In this paper, a modified projection algorithm is proposed in order to solve a common element of the solution set of monotone variational inequality and the fixed point set of a class of quasi-pseudo-contractive mapping. This algorithm requires the monotonicity and Lipschitz continuity of the mapping, but don’t need to know Lipschitz constant. On one hand, this algorithm does not compute the projection onto the feasible set at each iteration, on the other hand, the strong convergence of the sequence generated by the algorithm can be obtained without viscosity technology, and the convergence rate of the algorithm better than some algorithms, and the effect of the algorithm is illustrated by two numerical experiments. Quasi-pseudo-contractive mapping (dpeaa)DE-He213 Variational inequality (dpeaa)DE-He213 Monotonicity (dpeaa)DE-He213 Fixed point (dpeaa)DE-He213 Liu, Xiaolan (orcid)0000-0001-8904-6782 aut Deng, Jia aut Sun, Yan aut Enthalten in Journal of applied mathematics and computing Berlin : Springer, 2006 69(2023), 3 vom: 03. Apr., Seite 2717-2739 (DE-627)565516833 (DE-600)2424171-4 1865-2085 nnns volume:69 year:2023 number:3 day:03 month:04 pages:2717-2739 https://dx.doi.org/10.1007/s12190-023-01853-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 69 2023 3 03 04 2717-2739
spelling	10.1007/s12190-023-01853-z doi (DE-627)SPR051657066 (SPR)s12190-023-01853-z-e DE-627 ger DE-627 rakwb eng Zhang, Huan verfasserin aut An improved relaxed inertial projection algorithm for solving the minimum-norm solution of variational inequality and fixed point problems 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) under exclusive licence to Korean Society for Informatics and Computational Applied Mathematics 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In this paper, a modified projection algorithm is proposed in order to solve a common element of the solution set of monotone variational inequality and the fixed point set of a class of quasi-pseudo-contractive mapping. This algorithm requires the monotonicity and Lipschitz continuity of the mapping, but don’t need to know Lipschitz constant. On one hand, this algorithm does not compute the projection onto the feasible set at each iteration, on the other hand, the strong convergence of the sequence generated by the algorithm can be obtained without viscosity technology, and the convergence rate of the algorithm better than some algorithms, and the effect of the algorithm is illustrated by two numerical experiments. Quasi-pseudo-contractive mapping (dpeaa)DE-He213 Variational inequality (dpeaa)DE-He213 Monotonicity (dpeaa)DE-He213 Fixed point (dpeaa)DE-He213 Liu, Xiaolan (orcid)0000-0001-8904-6782 aut Deng, Jia aut Sun, Yan aut Enthalten in Journal of applied mathematics and computing Berlin : Springer, 2006 69(2023), 3 vom: 03. Apr., Seite 2717-2739 (DE-627)565516833 (DE-600)2424171-4 1865-2085 nnns volume:69 year:2023 number:3 day:03 month:04 pages:2717-2739 https://dx.doi.org/10.1007/s12190-023-01853-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 69 2023 3 03 04 2717-2739
allfields_unstemmed	10.1007/s12190-023-01853-z doi (DE-627)SPR051657066 (SPR)s12190-023-01853-z-e DE-627 ger DE-627 rakwb eng Zhang, Huan verfasserin aut An improved relaxed inertial projection algorithm for solving the minimum-norm solution of variational inequality and fixed point problems 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) under exclusive licence to Korean Society for Informatics and Computational Applied Mathematics 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In this paper, a modified projection algorithm is proposed in order to solve a common element of the solution set of monotone variational inequality and the fixed point set of a class of quasi-pseudo-contractive mapping. This algorithm requires the monotonicity and Lipschitz continuity of the mapping, but don’t need to know Lipschitz constant. On one hand, this algorithm does not compute the projection onto the feasible set at each iteration, on the other hand, the strong convergence of the sequence generated by the algorithm can be obtained without viscosity technology, and the convergence rate of the algorithm better than some algorithms, and the effect of the algorithm is illustrated by two numerical experiments. Quasi-pseudo-contractive mapping (dpeaa)DE-He213 Variational inequality (dpeaa)DE-He213 Monotonicity (dpeaa)DE-He213 Fixed point (dpeaa)DE-He213 Liu, Xiaolan (orcid)0000-0001-8904-6782 aut Deng, Jia aut Sun, Yan aut Enthalten in Journal of applied mathematics and computing Berlin : Springer, 2006 69(2023), 3 vom: 03. Apr., Seite 2717-2739 (DE-627)565516833 (DE-600)2424171-4 1865-2085 nnns volume:69 year:2023 number:3 day:03 month:04 pages:2717-2739 https://dx.doi.org/10.1007/s12190-023-01853-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 69 2023 3 03 04 2717-2739
allfieldsGer	10.1007/s12190-023-01853-z doi (DE-627)SPR051657066 (SPR)s12190-023-01853-z-e DE-627 ger DE-627 rakwb eng Zhang, Huan verfasserin aut An improved relaxed inertial projection algorithm for solving the minimum-norm solution of variational inequality and fixed point problems 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) under exclusive licence to Korean Society for Informatics and Computational Applied Mathematics 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In this paper, a modified projection algorithm is proposed in order to solve a common element of the solution set of monotone variational inequality and the fixed point set of a class of quasi-pseudo-contractive mapping. This algorithm requires the monotonicity and Lipschitz continuity of the mapping, but don’t need to know Lipschitz constant. On one hand, this algorithm does not compute the projection onto the feasible set at each iteration, on the other hand, the strong convergence of the sequence generated by the algorithm can be obtained without viscosity technology, and the convergence rate of the algorithm better than some algorithms, and the effect of the algorithm is illustrated by two numerical experiments. Quasi-pseudo-contractive mapping (dpeaa)DE-He213 Variational inequality (dpeaa)DE-He213 Monotonicity (dpeaa)DE-He213 Fixed point (dpeaa)DE-He213 Liu, Xiaolan (orcid)0000-0001-8904-6782 aut Deng, Jia aut Sun, Yan aut Enthalten in Journal of applied mathematics and computing Berlin : Springer, 2006 69(2023), 3 vom: 03. Apr., Seite 2717-2739 (DE-627)565516833 (DE-600)2424171-4 1865-2085 nnns volume:69 year:2023 number:3 day:03 month:04 pages:2717-2739 https://dx.doi.org/10.1007/s12190-023-01853-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 69 2023 3 03 04 2717-2739
allfieldsSound	10.1007/s12190-023-01853-z doi (DE-627)SPR051657066 (SPR)s12190-023-01853-z-e DE-627 ger DE-627 rakwb eng Zhang, Huan verfasserin aut An improved relaxed inertial projection algorithm for solving the minimum-norm solution of variational inequality and fixed point problems 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) under exclusive licence to Korean Society for Informatics and Computational Applied Mathematics 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In this paper, a modified projection algorithm is proposed in order to solve a common element of the solution set of monotone variational inequality and the fixed point set of a class of quasi-pseudo-contractive mapping. This algorithm requires the monotonicity and Lipschitz continuity of the mapping, but don’t need to know Lipschitz constant. On one hand, this algorithm does not compute the projection onto the feasible set at each iteration, on the other hand, the strong convergence of the sequence generated by the algorithm can be obtained without viscosity technology, and the convergence rate of the algorithm better than some algorithms, and the effect of the algorithm is illustrated by two numerical experiments. Quasi-pseudo-contractive mapping (dpeaa)DE-He213 Variational inequality (dpeaa)DE-He213 Monotonicity (dpeaa)DE-He213 Fixed point (dpeaa)DE-He213 Liu, Xiaolan (orcid)0000-0001-8904-6782 aut Deng, Jia aut Sun, Yan aut Enthalten in Journal of applied mathematics and computing Berlin : Springer, 2006 69(2023), 3 vom: 03. Apr., Seite 2717-2739 (DE-627)565516833 (DE-600)2424171-4 1865-2085 nnns volume:69 year:2023 number:3 day:03 month:04 pages:2717-2739 https://dx.doi.org/10.1007/s12190-023-01853-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 69 2023 3 03 04 2717-2739
language	English
source	Enthalten in Journal of applied mathematics and computing 69(2023), 3 vom: 03. Apr., Seite 2717-2739 volume:69 year:2023 number:3 day:03 month:04 pages:2717-2739
sourceStr	Enthalten in Journal of applied mathematics and computing 69(2023), 3 vom: 03. Apr., Seite 2717-2739 volume:69 year:2023 number:3 day:03 month:04 pages:2717-2739
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Quasi-pseudo-contractive mapping Variational inequality Monotonicity Fixed point
isfreeaccess_bool	false
container_title	Journal of applied mathematics and computing
authorswithroles_txt_mv	Zhang, Huan @@aut@@ Liu, Xiaolan @@aut@@ Deng, Jia @@aut@@ Sun, Yan @@aut@@
publishDateDaySort_date	2023-04-03T00:00:00Z
hierarchy_top_id	565516833
id	SPR051657066
language_de	englisch
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Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract In this paper, a modified projection algorithm is proposed in order to solve a common element of the solution set of monotone variational inequality and the fixed point set of a class of quasi-pseudo-contractive mapping. This algorithm requires the monotonicity and Lipschitz continuity of the mapping, but don’t need to know Lipschitz constant. 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author	Zhang, Huan
spellingShingle	Zhang, Huan misc Quasi-pseudo-contractive mapping misc Variational inequality misc Monotonicity misc Fixed point An improved relaxed inertial projection algorithm for solving the minimum-norm solution of variational inequality and fixed point problems
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topic_title	An improved relaxed inertial projection algorithm for solving the minimum-norm solution of variational inequality and fixed point problems Quasi-pseudo-contractive mapping (dpeaa)DE-He213 Variational inequality (dpeaa)DE-He213 Monotonicity (dpeaa)DE-He213 Fixed point (dpeaa)DE-He213
topic	misc Quasi-pseudo-contractive mapping misc Variational inequality misc Monotonicity misc Fixed point
topic_unstemmed	misc Quasi-pseudo-contractive mapping misc Variational inequality misc Monotonicity misc Fixed point
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title	An improved relaxed inertial projection algorithm for solving the minimum-norm solution of variational inequality and fixed point problems
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title_full	An improved relaxed inertial projection algorithm for solving the minimum-norm solution of variational inequality and fixed point problems
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title_sort	improved relaxed inertial projection algorithm for solving the minimum-norm solution of variational inequality and fixed point problems
title_auth	An improved relaxed inertial projection algorithm for solving the minimum-norm solution of variational inequality and fixed point problems
abstract	Abstract In this paper, a modified projection algorithm is proposed in order to solve a common element of the solution set of monotone variational inequality and the fixed point set of a class of quasi-pseudo-contractive mapping. This algorithm requires the monotonicity and Lipschitz continuity of the mapping, but don’t need to know Lipschitz constant. On one hand, this algorithm does not compute the projection onto the feasible set at each iteration, on the other hand, the strong convergence of the sequence generated by the algorithm can be obtained without viscosity technology, and the convergence rate of the algorithm better than some algorithms, and the effect of the algorithm is illustrated by two numerical experiments. © The Author(s) under exclusive licence to Korean Society for Informatics and Computational Applied Mathematics 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
abstractGer	Abstract In this paper, a modified projection algorithm is proposed in order to solve a common element of the solution set of monotone variational inequality and the fixed point set of a class of quasi-pseudo-contractive mapping. This algorithm requires the monotonicity and Lipschitz continuity of the mapping, but don’t need to know Lipschitz constant. On one hand, this algorithm does not compute the projection onto the feasible set at each iteration, on the other hand, the strong convergence of the sequence generated by the algorithm can be obtained without viscosity technology, and the convergence rate of the algorithm better than some algorithms, and the effect of the algorithm is illustrated by two numerical experiments. © The Author(s) under exclusive licence to Korean Society for Informatics and Computational Applied Mathematics 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
abstract_unstemmed	Abstract In this paper, a modified projection algorithm is proposed in order to solve a common element of the solution set of monotone variational inequality and the fixed point set of a class of quasi-pseudo-contractive mapping. This algorithm requires the monotonicity and Lipschitz continuity of the mapping, but don’t need to know Lipschitz constant. On one hand, this algorithm does not compute the projection onto the feasible set at each iteration, on the other hand, the strong convergence of the sequence generated by the algorithm can be obtained without viscosity technology, and the convergence rate of the algorithm better than some algorithms, and the effect of the algorithm is illustrated by two numerical experiments. © The Author(s) under exclusive licence to Korean Society for Informatics and Computational Applied Mathematics 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
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container_issue	3
title_short	An improved relaxed inertial projection algorithm for solving the minimum-norm solution of variational inequality and fixed point problems
url	https://dx.doi.org/10.1007/s12190-023-01853-z
remote_bool	true
author2	Liu, Xiaolan Deng, Jia Sun, Yan
author2Str	Liu, Xiaolan Deng, Jia Sun, Yan
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doi_str	10.1007/s12190-023-01853-z
up_date	2024-07-03T23:06:18.206Z
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An improved relaxed inertial projection algorithm for solving the minimum-norm solution of variational inequality and fixed point problems

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