Continuous-time algorithm design for distributed constrained optimization over weight-balanced directed networks
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TP18;O224

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    Abstract:

    This paper investigates a distributed convex optimization with local constraint sets over weight-balanced directed networks,where the global objective function is described as a sum of some agents' local objective functions.To solve this problem in a distributed way,the problem is transformed into a Fenchel dual problem by introducing local conjugate functions.Then,for the Fenchel dual problem,a distributed continuous-time algorithm is proposed based on the singular perturbation system.When the local objective functions are strongly convex and their gradients are Lipschitz continuous,it is shown that the primal and dual optimality can be both achieved by using the tools from convex analysis and Lyapunov stability.Finally,simulation results are given to illustrate the effectiveness of the proposed algorithm.

    Reference
    [1] Nedic A,Ozdaglar A.Distributed subgradient methods for multi-agent optimization[J].IEEE Transactions on Automatic Control,2009,54(1):48-61
    [2] Nedic A,Ozdaglar A,Parrilo P A.Constrained consensus and optimization in multi-agent networks[J].IEEE Transactions on Automatic Control,2010,55(4):922-938
    [3] Zhu M H,Martinez S.On distributed convex optimization under inequality and equality constraints[J].IEEE Transactions on Automatic Control,2012,57(1):151-164
    [4] Chang T H,Nedić A,Scaglione A.Distributed constrained optimization by consensus-based primal-dual perturbation method[J].IEEE Transactions on Automatic Control,2014,59(6):1524-1538
    [5] Yuan D M,Ho D W C,Xu S Y.Regularized primal:dual subgradient method for distributed constrained optimization[J].IEEE Transactions on Cybernetics,2016,46(9):2109-2118
    [6] Mateos-Núñez D,Cortés J.Distributed saddle-point subgradient algorithms with laplacian averaging[J].IEEE Transactions on Automatic Control,2017,62(6):2720-2735
    [7] Lee S,Zavlanos M M.Approximate projection methods for decentralized optimization with functional constraints[J].IEEE Transactions on Automatic Control,2018,63(10):3248-3260
    [8] You K Y,Tempo R,Xie P.Distributed algorithms for robust convex optimization via the scenario approach[J].IEEE Transactions on Automatic Control,2019,64(3):880-895
    [9] Lu J,Tang C Y.Zero-gradient-sum algorithms for distributed convex optimization:the continuous-time case[J].IEEE Transactions on Automatic Control,2012,57(9):2348-2354
    [10] Varagnolo D,Zanella F,Cenedese A,et al.Newton-raphson consensus for distributed convex optimization[J].IEEE Transactions on Automatic Control,2016,61(4):994-1009
    [11] Gharesifard B,Cortés J.Distributed continuous-time convex optimization on weight-balanced digraphs[J].IEEE Transactions on Automatic Control,2014,59(3):781-786
    [12] Kia S S,Cortés J,Martínez S.Distributed convex optimization via continuous-time coordination algorithms with discrete-time communication[J].Automatica,2015,55:254-264
    [13] Li Z H,Ding Z T,Sun J Y,et al.Distributed adaptive convex optimization on directed graphs via continuous-time algorithms[J].IEEE Transactions on Automatic Control,2018,63(5):1434-1441
    [14] Zhu Y N,Yu W W,Wen G H,et al.Continuous-time coordination algorithm for distributed convex optimization over weight-unbalanced directed networks[J].IEEE Transactions on Circuits and Systems Ⅱ:Express Briefs,2019,66(7):1202-1206
    [15] Liu Q S,Wang J.A second-order multi-agent network for bound-constrained distributed optimization[J].IEEE Transactions on Automatic Control,2015,60(12):3310-3315
    [16] Zeng X L,Yi P,Hong Y G.Distributed continuous-time algorithm for constrained convex optimizations via nonsmooth analysis approach[J].IEEE Transactions on Automatic Control,2017,62(10):5227-5233
    [17] Liu Q S,Yang S F,Wang J.A collective neurodynamic approach to distributed constrained optimization[J].IEEE Transactions on Neural Networks and Learning Systems,2017,28(8):1747-1758
    [18] Yang S F,Liu Q S,Wang J.A multi-agent system with a proportional-integral protocol for distributed constrained optimization[J].IEEE Transactions on Automatic Control,2017,62(7):3461-3467
    [19] Zhu Y N,Yu W W,Wen G H,et al.Continuous-time distributed subgradient algorithm for convex optimization with general constraints[J].IEEE Transactions on Automatic Control,2019,64(4):1694-1701
    [20] Zhu Y N,Yu W W,Wen G H,et al.Projected primal:dual dynamics for distributed constrained nonsmooth convex optimization[J].IEEE Transactions on Cybernetics,2020,50(4):1776-1782
    [21] 衣鹏,洪奕光.分布式合作优化及其应用[J].中国科学:数学,2016,46(10):1547-1564 YI Peng,HONG Yiguang.Distributed cooperative optimization and its applications[J].Scientia Sinica (Mathematica),2016,46(10):1547-1564
    [22] 谢佩,游科友,洪奕光,等.网络化分布式凸优化算法研究进展[J].控制理论与应用,2018,35(7):918-927 XIE Pei,YOU Keyou,HONG Yiguang,et al.A survey of distributed convex optimization algorithms over networks[J].Control Theory & Applications,2018,35(7):918-927
    [23] Yang T,Yi X,Wu J,et al.A survey of distributed optimization[J].Annual Reviews in Control,2019,47:278-305
    [24] Wu X Y,Lu J.Fenchel dual gradient methods for distributed convex optimization over time-varying networks[C]//2017 IEEE 56th Annual Conference on Decision and Control (CDC),2017:2894-2899
    [25] Wu X Y,Lu J.Fenchel dual gradient methods for distributed convex optimization over time-varying networks[J].IEEE Transactions on Automatic Control,2019,64(11):4629-4636
    [26] Bertsekas D P.Nonlinear programming[M].Belmont,MA,USA:Athena Scientific,1999
    [27] Ruszczyński A P.Nonlinear optimization[M].Boca Raton,FL:Princeton University Press,2006
    [28] Nesterov Y.Introductory lectures on convex optimization[M].Boston,MA:Springer US,2004
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ZHU Yanan, WEN Guanghui. Continuous-time algorithm design for distributed constrained optimization over weight-balanced directed networks[J]. Journal of Nanjing University of Information Science & Technology,2020,12(5):549-555

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  • Received:July 01,2020
  • Online: October 29,2020
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