Weighted Network Design With Cardinality Constraints via Alternating Direction Method of Multipliers

This paper examines simultaneous design of the network topology and the corresponding edge weights in the presence of a cardinality constraint on the edge set. Network properties of interest for this design problem lead to optimization formulations with convex objectives, convex constraint sets, and cardinality constraints. This class of problems is referred to as the cardinality-constrained optimization problem (CCOP); the cardinality constraint generally makes CCOPs NP-hard. In this paper, a customized alternating direction method of multipliers (ADMM) algorithm aiming to improve the scalability of the solution strategy for large-scale CCOPs is proposed. This algorithm utilizes the special structure of the problem formulation to obtain closed-form solutions during each iterative step of the corresponding ADMM updates. We also provide a convergence proof of the proposed customized ADMM to a stationary point under certain conditions. Simulation results illustrate that the customized ADMM algorithm has a significant computational advantage over existing methods, particularly for large-scale network design problems.

[1]  Mehran Mesbahi,et al.  Network Topology Design for UAV Swarming with Wind Gusts , 2011 .

[2]  Stephen P. Boyd,et al.  Minimizing Effective Resistance of a Graph , 2008, SIAM Rev..

[3]  Reza Olfati-Saber,et al.  Consensus and Cooperation in Networked Multi-Agent Systems , 2007, Proceedings of the IEEE.

[4]  Reza Olfati-Saber,et al.  Flocking for multi-agent dynamic systems: algorithms and theory , 2006, IEEE Transactions on Automatic Control.

[5]  Tom Goldstein,et al.  The Split Bregman Method for L1-Regularized Problems , 2009, SIAM J. Imaging Sci..

[6]  Juan C. Agüero,et al.  Low-order control design using a novel rank-constrained optimization approach , 2016, 2016 Australian Control Conference (AuCC).

[7]  Zhi-Quan Luo,et al.  On the linear convergence of the alternating direction method of multipliers , 2012, Mathematical Programming.

[8]  Stephen P. Boyd,et al.  Fast linear iterations for distributed averaging , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[9]  Alejandro Ribeiro,et al.  Consensus in Ad Hoc WSNs With Noisy Links—Part I: Distributed Estimation of Deterministic Signals , 2008, IEEE Transactions on Signal Processing.

[10]  Stephen P. Boyd,et al.  Distributed average consensus with least-mean-square deviation , 2007, J. Parallel Distributed Comput..

[11]  Duan Li,et al.  Cardinality Constrained Linear-Quadratic Optimal Control , 2011, IEEE Transactions on Automatic Control.

[12]  Amir G. Aghdam,et al.  Generalized algebraic connectivity for asymmetric networks , 2016, 2016 American Control Conference (ACC).

[13]  Robert J. Vanderbei,et al.  An Interior-Point Method for Semidefinite Programming , 1996, SIAM J. Optim..

[14]  George J. Pappas,et al.  Potential Fields for Maintaining Connectivity of Mobile Networks , 2007, IEEE Transactions on Robotics.

[15]  Shiqian Ma,et al.  Alternating direction method of multipliers for real and complex polynomial optimization models , 2014 .

[16]  Fuzhen Zhang Matrix Theory: Basic Results and Techniques , 1999 .

[17]  Stephen P. Boyd,et al.  Enhancing Sparsity by Reweighted ℓ1 Minimization , 2007, 0711.1612.

[18]  Emmanuel J. Candès,et al.  Decoding by linear programming , 2005, IEEE Transactions on Information Theory.

[19]  L. El Ghaoui,et al.  Designing node and edge weights of a graph to meet Laplacian eigenvalue constraints , 2010, 2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[20]  Mihailo R. Jovanovic,et al.  On the design of optimal structured and sparse feedback gains via sequential convex programming , 2014, 2014 American Control Conference.

[21]  B. Borchers CSDP, A C library for semidefinite programming , 1999 .

[22]  C. Lucas,et al.  Heuristic algorithms for the cardinality constrained efficient frontier , 2011, Eur. J. Oper. Res..

[23]  John N. Tsitsiklis,et al.  Parallel and distributed computation , 1989 .

[24]  Xiangfeng Wang,et al.  Nonnegative matrix factorization using ADMM: Algorithm and convergence analysis , 2016, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[25]  Randal W. Beard,et al.  A coordination architecture for spacecraft formation control , 2001, IEEE Trans. Control. Syst. Technol..

[26]  Jérôme Malick,et al.  Clarke Generalized Jacobian of the Projection onto the Cone of Positive Semidefinite Matrices , 2006 .

[27]  Wotao Yin,et al.  Bregman Iterative Algorithms for (cid:2) 1 -Minimization with Applications to Compressed Sensing ∗ , 2008 .

[28]  Ran Dai,et al.  Optimal Trajectory Generation for Establishing Connectivity in Proximity Networks , 2013, IEEE Transactions on Aerospace and Electronic Systems.

[29]  Stephen P. Boyd,et al.  Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers , 2011, Found. Trends Mach. Learn..

[30]  Zhi-Quan Luo,et al.  Convergence analysis of alternating direction method of multipliers for a family of nonconvex problems , 2015, ICASSP.

[31]  Fu Lin,et al.  Design of Optimal Sparse Feedback Gains via the Alternating Direction Method of Multipliers , 2011, IEEE Transactions on Automatic Control.

[32]  Dimitris Bertsimas,et al.  Algorithm for cardinality-constrained quadratic optimization , 2009, Comput. Optim. Appl..

[33]  Ran Dai,et al.  Optimal topology design for dynamic networks , 2011, IEEE Conference on Decision and Control and European Control Conference.

[34]  Shiqian Ma,et al.  On the Global Linear Convergence of the ADMM with MultiBlock Variables , 2014, SIAM J. Optim..

[35]  Magnus Egerstedt,et al.  Graph Theoretic Methods in Multiagent Networks , 2010, Princeton Series in Applied Mathematics.

[36]  Wotao Yin,et al.  A Fixed-Point Continuation Method for L_1-Regularization with Application to Compressed Sensing , 2007 .

[37]  Sepideh Hassan-Moghaddam,et al.  Topology Design for Stochastically Forced Consensus Networks , 2018, IEEE Transactions on Control of Network Systems.

[38]  Carlo Fischione,et al.  On the Convergence of Alternating Direction Lagrangian Methods for Nonconvex Structured Optimization Problems , 2014, IEEE Transactions on Control of Network Systems.

[39]  Tucker R. Balch,et al.  Behavior-based formation control for multirobot teams , 1998, IEEE Trans. Robotics Autom..