A penalty-like neurodynamic approach to constrained nonsmooth distributed convex optimization
A nonsmooth distributed optimization problem subject to affine equality and convex inequality is considered in this paper. All the local objective functions in the distributed optimization problem possess a common decision variable. And taking privacy into consideration, each agent doesn’t share its...
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| Vydáno v: | Neurocomputing (Amsterdam) Ročník 377; s. 225 - 233 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier B.V
15.02.2020
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| ISSN: | 0925-2312, 1872-8286 |
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| Abstract | A nonsmooth distributed optimization problem subject to affine equality and convex inequality is considered in this paper. All the local objective functions in the distributed optimization problem possess a common decision variable. And taking privacy into consideration, each agent doesn’t share its local information with other agents, including the information about the local objective function and constraint set. To cope with this distributed optimization, a neurodynamic approach based on the penalty-like methods is proposed. It is proved that the presented neurodynamic approach is convergent to an optimal solution to the considered distributed optimization problem. The proposed neurodynamic approach in this paper has lower model complexity and computational load via reducing auxiliary variables. In the end, two illustrative examples are given to show the effectiveness and practical application of the proposed neural network. |
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| AbstractList | A nonsmooth distributed optimization problem subject to affine equality and convex inequality is considered in this paper. All the local objective functions in the distributed optimization problem possess a common decision variable. And taking privacy into consideration, each agent doesn’t share its local information with other agents, including the information about the local objective function and constraint set. To cope with this distributed optimization, a neurodynamic approach based on the penalty-like methods is proposed. It is proved that the presented neurodynamic approach is convergent to an optimal solution to the considered distributed optimization problem. The proposed neurodynamic approach in this paper has lower model complexity and computational load via reducing auxiliary variables. In the end, two illustrative examples are given to show the effectiveness and practical application of the proposed neural network. |
| Author | Jiang, Xinrui Qin, Sitian Xue, Xiaoping |
| Author_xml | – sequence: 1 givenname: Xinrui surname: Jiang fullname: Jiang, Xinrui email: jiangxrhit@163.com organization: Department of Mathematics, Harbin Institute of Technology, Harbin 150001, China – sequence: 2 givenname: Sitian orcidid: 0000-0002-4543-4940 surname: Qin fullname: Qin, Sitian email: qinsitian@hitwh.edu.cn organization: Department of Mathematics, Harbin Institute of Technology, Weihai 264209, China – sequence: 3 givenname: Xiaoping surname: Xue fullname: Xue, Xiaoping email: xiaopingxue@hit.edu.cn organization: Department of Mathematics, Harbin Institute of Technology, Harbin 150001, China |
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| Cites_doi | 10.1016/j.automatica.2016.08.007 10.1016/j.neucom.2017.12.060 10.1016/j.sysconle.2015.06.006 10.1016/j.neucom.2018.01.082 10.1080/23307706.2014.926622 10.1109/TNN.2009.2016340 10.1016/j.neucom.2018.11.002 10.1109/TETCI.2017.2716377 10.1016/j.neucom.2017.09.079 10.1109/TCYB.2016.2567449 10.1016/j.automatica.2011.03.014 10.1016/j.neucom.2017.09.016 10.1109/TNNLS.2016.2549566 10.1109/TAC.2018.2810039 10.1109/TAC.2016.2628807 10.1109/TAC.2013.2278132 10.1109/TAC.2015.2416927 10.1109/TNN.2011.2109735 10.1016/j.neucom.2017.07.005 10.1016/j.neucom.2018.03.036 10.1109/TAC.2017.2673240 10.1109/TNN.2010.2050601 10.1109/TCYB.2017.2760908 |
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| References | Xue, Bian (bib0030) 2008; 55(8) Gharesifard, Cortes (bib0019) 2014; 59(3) Hu, Yang (bib0017) 2018; 287 Ma, Bian (bib0009) 2019 Qin, Yang, Xue, Song (bib0024) 2017; 47(10) Blot, Picard, Thome, Cord (bib0001) 2019; 330 Clarke (bib0029) 1983 Le, Yan, Xi (bib0002) 2017; 1(4) Liu, Yang, Wang (bib0004) 2017; 28(8) Le, Chen, Yan, Xi (bib0018) 2018; 48(11) Liu, Wang (bib0020) 2015; 60(12) Cheng, Hou, Tan, Lin (bib0011) 2010; 21(8) Cheng, Hou, Lin, Tan, Zhang, Wu (bib0031) 2011; 22(5) Yi, Hong, Liu (bib0012) 2015; 83(711) Dong, Wei, Liu, Alsaadi, Dong, Wei, Liu, Alsaadi, Dong, Wei (bib0014) 2018; 275 Droge, Kawashima, Egerstedt (bib0006) 2014; 1(3) Cheng, Hou, Lin, Tan, Zhang (bib0025) 2011; 47(10) Bian, Xue (bib0033) 2009; 20(6) Li, Zhang, Ji, Sun (bib0015) 2018; 275 Zhao, Gang, Dai (bib0008) 2018; 284 Zeng, Yi, Hong (bib0021) 2017; 62(10) Yi, Hong, Liu (bib0026) 2016; 74 Liu, Qin (bib0028) 2018 Aubin, Cellina (bib0032) 1984 Yan, Hui, Xia (bib0016) 2018; 296 Zhu, Yu, Wen, Chen, Ren (bib0022) 2018; 64(4) Zhou, Zeng, Hong (bib0027) 2018 Sun, Ye, Hu (bib0013) 2017; 62(7) Zhang, Lu, Zheng, Shuai, Yu, Li (bib0007) 2018; 63(12) Tran, Wang, Yang (bib0005) 2018; 272 Zhang, Kong, Zheng, Zhang, Qu, Liao, Yu (bib0010) 2018 Bullo, Cortes, Martinez (bib0003) 2009 Zhu, Yu, Wen, Chen (bib0023) 2018 Yi (10.1016/j.neucom.2019.10.050_bib0026) 2016; 74 Hu (10.1016/j.neucom.2019.10.050_bib0017) 2018; 287 Zeng (10.1016/j.neucom.2019.10.050_bib0021) 2017; 62(10) Sun (10.1016/j.neucom.2019.10.050_bib0013) 2017; 62(7) Li (10.1016/j.neucom.2019.10.050_bib0015) 2018; 275 Cheng (10.1016/j.neucom.2019.10.050_bib0031) 2011; 22(5) Zhu (10.1016/j.neucom.2019.10.050_sbref0023) 2018 Bian (10.1016/j.neucom.2019.10.050_bib0033) 2009; 20(6) Droge (10.1016/j.neucom.2019.10.050_bib0006) 2014; 1(3) Yi (10.1016/j.neucom.2019.10.050_bib0012) 2015; 83(711) Zhao (10.1016/j.neucom.2019.10.050_bib0008) 2018; 284 Yan (10.1016/j.neucom.2019.10.050_bib0016) 2018; 296 Zhou (10.1016/j.neucom.2019.10.050_bib0027) 2018 Xue (10.1016/j.neucom.2019.10.050_bib0030) 2008; 55(8) Liu (10.1016/j.neucom.2019.10.050_bib0020) 2015; 60(12) Cheng (10.1016/j.neucom.2019.10.050_bib0025) 2011; 47(10) Gharesifard (10.1016/j.neucom.2019.10.050_bib0019) 2014; 59(3) Zhang (10.1016/j.neucom.2019.10.050_bib0010) 2018 Liu (10.1016/j.neucom.2019.10.050_bib0028) 2018 Ma (10.1016/j.neucom.2019.10.050_bib0009) 2019 Cheng (10.1016/j.neucom.2019.10.050_bib0011) 2010; 21(8) Clarke (10.1016/j.neucom.2019.10.050_bib0029) 1983 Liu (10.1016/j.neucom.2019.10.050_bib0004) 2017; 28(8) Tran (10.1016/j.neucom.2019.10.050_bib0005) 2018; 272 Dong (10.1016/j.neucom.2019.10.050_bib0014) 2018; 275 Le (10.1016/j.neucom.2019.10.050_bib0002) 2017; 1(4) Le (10.1016/j.neucom.2019.10.050_bib0018) 2018; 48(11) Bullo (10.1016/j.neucom.2019.10.050_bib0003) 2009 Zhang (10.1016/j.neucom.2019.10.050_bib0007) 2018; 63(12) Zhu (10.1016/j.neucom.2019.10.050_bib0022) 2018; 64(4) Qin (10.1016/j.neucom.2019.10.050_bib0024) 2017; 47(10) Aubin (10.1016/j.neucom.2019.10.050_bib0032) 1984 Blot (10.1016/j.neucom.2019.10.050_bib0001) 2019; 330 |
| References_xml | – year: 2009 ident: bib0003 publication-title: Distributed Control of Robotic Networks: A Mathematical Approach to Motion Coordination Algorithms – volume: 275 start-page: 1416 year: 2018 end-page: 1425 ident: bib0015 article-title: Distributed multi-agent optimization via event-triggered based continuous-time Newton–Raphson algorithm publication-title: Neurocomputing – volume: 47(10) start-page: 3063 year: 2017 end-page: 3074 ident: bib0024 article-title: A one-layer recurrent neural network for pseudoconvex optimization problems with equality and inequality constraints publication-title: IEEE Trans. Cybern. – volume: 64(4) start-page: 1694 year: 2018 end-page: 1701 ident: bib0022 article-title: Continuous-time distributed subgradient algorithm for convex optimization with general constraints publication-title: IEEE Trans. Autom. Control – volume: 59(3) start-page: 781 year: 2014 end-page: 786 ident: bib0019 article-title: Distributed continuous-time convex optimization on weight-balanced digraphs publication-title: IEEE Trans. Autom. Control – volume: 22(5) start-page: 714 year: 2011 end-page: 726 ident: bib0031 article-title: Recurrent neural network for non-smooth convex optimization problems with application to the identification of genetic regulatory networks publication-title: IEEE Trans. Neural Netw. – volume: 296 start-page: 100 year: 2018 end-page: 108 ident: bib0016 article-title: Distributed optimization of multi-agent systems with delayed sampled-data publication-title: Neurocomputing – volume: 63(12) start-page: 4110 year: 2018 end-page: 4125 ident: bib0007 article-title: A new varying-parameter convergent-differential neural-network for solving time-varying convex QP problem constrained by linear-equality publication-title: IEEE Trans. Autom. Control – volume: 21(8) start-page: 1351 year: 2010 end-page: 1358 ident: bib0011 article-title: Neural-network-based adaptive leader-following control for multiagent systems with uncertainties publication-title: IEEE Trans. Neural Netw. – volume: 1(3) start-page: 191 year: 2014 end-page: 213 ident: bib0006 article-title: Continuous-time proportional-integral distributed optimisation for networked systems publication-title: J. Control Decis. – volume: 20(6) start-page: 1024 year: 2009 end-page: 1038 ident: bib0033 article-title: Subgradient-based neural networks for nonsmooth nonconvex optimization problems publication-title: IEEE Trans. Neural Netw. – volume: 74 start-page: 259 year: 2016 end-page: 269 ident: bib0026 article-title: Initialization-free distributed algorithms for optimal resource allocation with feasibility constraints and application to economic dispatch of power systems publication-title: Automatica – year: 2018 ident: bib0010 article-title: Robustness analysis of a power-type varying-parameter recurrent neural network for solving time-varying QM and QP problems and applications publication-title: IEEE Trans. Syst. Man Cybern.: Syst. – volume: 28(8) start-page: 1747 year: 2017 end-page: 1758 ident: bib0004 article-title: A collective neurodynamic approach to distributed constrained optimization publication-title: IEEE Trans. Neural Netw. Learn. Syst. – volume: 60(12) start-page: 3310 year: 2015 end-page: 3315 ident: bib0020 article-title: A second-order multi-agent network for bound-constrained distributed optimization publication-title: IEEE Trans. Autom. Control – volume: 287 start-page: 173 year: 2018 end-page: 184 ident: bib0017 article-title: Distributed finite-time optimization for second order continuous-time multiple agents systems with time-varying cost function publication-title: Neurocomputing – volume: 62(7) start-page: 3687 year: 2017 end-page: 3694 ident: bib0013 article-title: Distributed time-varying quadratic optimization for multiple agents under undirected graphs publication-title: IEEE Trans. Autom. Control – volume: 275 start-page: 725 year: 2018 end-page: 732 ident: bib0014 article-title: A modified distributed optimization method for both continuous-time and discrete-time multi-agent systems publication-title: Neurocomputing – year: 1983 ident: bib0029 publication-title: Optimization and Nonsmooth Analysis – volume: 272 start-page: 386 year: 2018 end-page: 395 ident: bib0005 article-title: Distributed optimization problem for double-integrator systems with the presence of the exogenous disturbance publication-title: Neurocomputing – volume: 1(4) start-page: 305 year: 2017 end-page: 314 ident: bib0002 article-title: A collective neurodynamic system for distributed optimization with applications in model predictive control publication-title: IEEE Trans. Emerg. Top. Comput. Intell. – volume: 55(8) start-page: 2378 year: 2008 end-page: 2391 ident: bib0030 article-title: Subgradient-based neural networks for nonsmooth convex optimization problems publication-title: IEEE Trans. Circuits Syst. I: Regul. Pap. – year: 2018 ident: bib0027 article-title: Adaptive exact penalty design for constrained distributed optimization publication-title: Trans. Autom. Control – year: 2018 ident: bib0028 article-title: A novel neurodynamic approach to constrained complex-variable pseudoconvex optimization publication-title: IEEE Trans. Cybern. – year: 2019 ident: bib0009 article-title: A novel multiagent neurodynamic approach to constrained distributed convex optimization publication-title: IEEE Trans. Cybern. – volume: 47(10) start-page: 2218 year: 2011 end-page: 2223 ident: bib0025 article-title: Solving a modified consensus problem of linear multi-agent systems publication-title: Automatica – volume: 83(711) start-page: 45 year: 2015 end-page: 52 ident: bib0012 article-title: Distributed gradient algorithm for constrained optimization with application to load sharing in power systems publication-title: Syst. Control Lett. – volume: 62(10) start-page: 5227 year: 2017 end-page: 5233 ident: bib0021 article-title: Distributed continuous-time algorithm for constrained convex optimizations via nonsmooth analysis approach publication-title: IEEE Trans. Autom. Control – volume: 330 start-page: 287 year: 2019 end-page: 296 ident: bib0001 article-title: Distributed optimization for deep learning with gossip exchange publication-title: Neurocomputing – volume: 284 start-page: 90 year: 2018 end-page: 98 ident: bib0008 article-title: Distributed event-triggered scheme for a convex optimization problem in multi-agent systems publication-title: Neurocomputing – year: 2018 ident: bib0023 article-title: Projected primal-dual dynamics for distributed constrained nonsmooth convex optimization publication-title: IEEE Trans. Cybern. – year: 1984 ident: bib0032 publication-title: Differential Inclusions – volume: 48(11) start-page: 3149 year: 2018 end-page: 3158 ident: bib0018 article-title: A neurodynamic approach to distributed optimization with globally coupled constraints publication-title: IEEE Trans. Cybern. – volume: 74 start-page: 259 year: 2016 ident: 10.1016/j.neucom.2019.10.050_bib0026 article-title: Initialization-free distributed algorithms for optimal resource allocation with feasibility constraints and application to economic dispatch of power systems publication-title: Automatica doi: 10.1016/j.automatica.2016.08.007 – volume: 284 start-page: 90 year: 2018 ident: 10.1016/j.neucom.2019.10.050_bib0008 article-title: Distributed event-triggered scheme for a convex optimization problem in multi-agent systems publication-title: Neurocomputing doi: 10.1016/j.neucom.2017.12.060 – volume: 83(711) start-page: 45 year: 2015 ident: 10.1016/j.neucom.2019.10.050_bib0012 article-title: Distributed gradient algorithm for constrained optimization with application to load sharing in power systems publication-title: Syst. Control Lett. doi: 10.1016/j.sysconle.2015.06.006 – volume: 287 start-page: 173 year: 2018 ident: 10.1016/j.neucom.2019.10.050_bib0017 article-title: Distributed finite-time optimization for second order continuous-time multiple agents systems with time-varying cost function publication-title: Neurocomputing doi: 10.1016/j.neucom.2018.01.082 – year: 2019 ident: 10.1016/j.neucom.2019.10.050_bib0009 article-title: A novel multiagent neurodynamic approach to constrained distributed convex optimization publication-title: IEEE Trans. Cybern. – volume: 1(3) start-page: 191 year: 2014 ident: 10.1016/j.neucom.2019.10.050_bib0006 article-title: Continuous-time proportional-integral distributed optimisation for networked systems publication-title: J. Control Decis. doi: 10.1080/23307706.2014.926622 – year: 2009 ident: 10.1016/j.neucom.2019.10.050_bib0003 – volume: 20(6) start-page: 1024 year: 2009 ident: 10.1016/j.neucom.2019.10.050_bib0033 article-title: Subgradient-based neural networks for nonsmooth nonconvex optimization problems publication-title: IEEE Trans. Neural Netw. doi: 10.1109/TNN.2009.2016340 – volume: 330 start-page: 287 year: 2019 ident: 10.1016/j.neucom.2019.10.050_bib0001 article-title: Distributed optimization for deep learning with gossip exchange publication-title: Neurocomputing doi: 10.1016/j.neucom.2018.11.002 – volume: 55(8) start-page: 2378 year: 2008 ident: 10.1016/j.neucom.2019.10.050_bib0030 article-title: Subgradient-based neural networks for nonsmooth convex optimization problems publication-title: IEEE Trans. Circuits Syst. I: Regul. Pap. – volume: 1(4) start-page: 305 year: 2017 ident: 10.1016/j.neucom.2019.10.050_bib0002 article-title: A collective neurodynamic system for distributed optimization with applications in model predictive control publication-title: IEEE Trans. Emerg. Top. Comput. Intell. doi: 10.1109/TETCI.2017.2716377 – volume: 275 start-page: 1416 year: 2018 ident: 10.1016/j.neucom.2019.10.050_bib0015 article-title: Distributed multi-agent optimization via event-triggered based continuous-time Newton–Raphson algorithm publication-title: Neurocomputing doi: 10.1016/j.neucom.2017.09.079 – year: 2018 ident: 10.1016/j.neucom.2019.10.050_bib0010 article-title: Robustness analysis of a power-type varying-parameter recurrent neural network for solving time-varying QM and QP problems and applications publication-title: IEEE Trans. Syst. Man Cybern.: Syst. – volume: 47(10) start-page: 3063 year: 2017 ident: 10.1016/j.neucom.2019.10.050_bib0024 article-title: A one-layer recurrent neural network for pseudoconvex optimization problems with equality and inequality constraints publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2016.2567449 – year: 2018 ident: 10.1016/j.neucom.2019.10.050_bib0028 article-title: A novel neurodynamic approach to constrained complex-variable pseudoconvex optimization publication-title: IEEE Trans. Cybern. – volume: 47(10) start-page: 2218 year: 2011 ident: 10.1016/j.neucom.2019.10.050_bib0025 article-title: Solving a modified consensus problem of linear multi-agent systems publication-title: Automatica doi: 10.1016/j.automatica.2011.03.014 – volume: 275 start-page: 725 year: 2018 ident: 10.1016/j.neucom.2019.10.050_bib0014 article-title: A modified distributed optimization method for both continuous-time and discrete-time multi-agent systems publication-title: Neurocomputing doi: 10.1016/j.neucom.2017.09.016 – year: 2018 ident: 10.1016/j.neucom.2019.10.050_sbref0023 article-title: Projected primal-dual dynamics for distributed constrained nonsmooth convex optimization publication-title: IEEE Trans. Cybern. – volume: 28(8) start-page: 1747 year: 2017 ident: 10.1016/j.neucom.2019.10.050_bib0004 article-title: A collective neurodynamic approach to distributed constrained optimization publication-title: IEEE Trans. Neural Netw. Learn. Syst. doi: 10.1109/TNNLS.2016.2549566 – volume: 63(12) start-page: 4110 year: 2018 ident: 10.1016/j.neucom.2019.10.050_bib0007 article-title: A new varying-parameter convergent-differential neural-network for solving time-varying convex QP problem constrained by linear-equality publication-title: IEEE Trans. Autom. Control doi: 10.1109/TAC.2018.2810039 – volume: 62(10) start-page: 5227 year: 2017 ident: 10.1016/j.neucom.2019.10.050_bib0021 article-title: Distributed continuous-time algorithm for constrained convex optimizations via nonsmooth analysis approach publication-title: IEEE Trans. Autom. Control doi: 10.1109/TAC.2016.2628807 – volume: 59(3) start-page: 781 year: 2014 ident: 10.1016/j.neucom.2019.10.050_bib0019 article-title: Distributed continuous-time convex optimization on weight-balanced digraphs publication-title: IEEE Trans. Autom. Control doi: 10.1109/TAC.2013.2278132 – volume: 60(12) start-page: 3310 year: 2015 ident: 10.1016/j.neucom.2019.10.050_bib0020 article-title: A second-order multi-agent network for bound-constrained distributed optimization publication-title: IEEE Trans. Autom. Control doi: 10.1109/TAC.2015.2416927 – year: 2018 ident: 10.1016/j.neucom.2019.10.050_bib0027 article-title: Adaptive exact penalty design for constrained distributed optimization publication-title: Trans. Autom. Control – year: 1984 ident: 10.1016/j.neucom.2019.10.050_bib0032 – volume: 22(5) start-page: 714 year: 2011 ident: 10.1016/j.neucom.2019.10.050_bib0031 article-title: Recurrent neural network for non-smooth convex optimization problems with application to the identification of genetic regulatory networks publication-title: IEEE Trans. Neural Netw. doi: 10.1109/TNN.2011.2109735 – volume: 272 start-page: 386 year: 2018 ident: 10.1016/j.neucom.2019.10.050_bib0005 article-title: Distributed optimization problem for double-integrator systems with the presence of the exogenous disturbance publication-title: Neurocomputing doi: 10.1016/j.neucom.2017.07.005 – volume: 296 start-page: 100 year: 2018 ident: 10.1016/j.neucom.2019.10.050_bib0016 article-title: Distributed optimization of multi-agent systems with delayed sampled-data publication-title: Neurocomputing doi: 10.1016/j.neucom.2018.03.036 – volume: 62(7) start-page: 3687 year: 2017 ident: 10.1016/j.neucom.2019.10.050_bib0013 article-title: Distributed time-varying quadratic optimization for multiple agents under undirected graphs publication-title: IEEE Trans. Autom. Control doi: 10.1109/TAC.2017.2673240 – volume: 64(4) start-page: 1694 year: 2018 ident: 10.1016/j.neucom.2019.10.050_bib0022 article-title: Continuous-time distributed subgradient algorithm for convex optimization with general constraints publication-title: IEEE Trans. Autom. Control – volume: 21(8) start-page: 1351 year: 2010 ident: 10.1016/j.neucom.2019.10.050_bib0011 article-title: Neural-network-based adaptive leader-following control for multiagent systems with uncertainties publication-title: IEEE Trans. Neural Netw. doi: 10.1109/TNN.2010.2050601 – year: 1983 ident: 10.1016/j.neucom.2019.10.050_bib0029 – volume: 48(11) start-page: 3149 year: 2018 ident: 10.1016/j.neucom.2019.10.050_bib0018 article-title: A neurodynamic approach to distributed optimization with globally coupled constraints publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2017.2760908 |
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| SubjectTerms | Constrained distributed optimization Differential inclusion Neurodynamic approach |
| Title | A penalty-like neurodynamic approach to constrained nonsmooth distributed convex optimization |
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