Minimization methods for non-differentiable functions
Minimization methods for non-differentiable functions
A class of convergent primal-dual subgradient algorithms for decomposable convex programs
Mathematical Programming: Series A and B
Convergence of a generalized subgradient method for nondifferentiable convex optimization
Mathematical Programming: Series A and B
Mixed-integer bilinear programming problems
Mathematical Programming: Series A and B
Optimal peer selection for minimum-delay peer-to-peer streaming with rateless codes
Proceedings of the ACM workshop on Advances in peer-to-peer multimedia streaming
On achieving maximum multicast throughput in undirected networks
IEEE/ACM Transactions on Networking (TON) - Special issue on networking and information theory
Minimum-cost multicast over coded packet networks
IEEE/ACM Transactions on Networking (TON) - Special issue on networking and information theory
Scalable streaming for heterogeneous clients
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Enhancing Lagrangian Dual Optimization for Linear Programs by Obviating Nondifferentiability
INFORMS Journal on Computing
rStream: Resilient and Optimal Peer-to-Peer Streaming with Rateless Codes
IEEE Transactions on Parallel and Distributed Systems
Scalable on-demand media streaming for heterogeneous clients
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
A merit function approach to the subgradient method with averaging
Optimization Methods & Software
Benders decomposition, Lagrangean relaxation and metaheuristic design
Journal of Heuristics
Optimized multipath network coding in lossy wireless networks
IEEE Journal on Selected Areas in Communications - Special issue on network coding for wireless communication networks
Processor speed control with thermal constraints
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Sender-based resource allocation for multi-hop routing networks
SARNOFF'09 Proceedings of the 32nd international conference on Sarnoff symposium
Backhaul and Routing Assignments with End-to-End QoS Constraints for Wireless Mesh Networks
Wireless Personal Communications: An International Journal
Optimal rate allocation in overlay content distribution
NETWORKING'07 Proceedings of the 6th international IFIP-TC6 conference on Ad Hoc and sensor networks, wireless networks, next generation internet
A subgradient optimization approach to inter-domain routing in IP/MPLS networks
NETWORKING'07 Proceedings of the 6th international IFIP-TC6 conference on Ad Hoc and sensor networks, wireless networks, next generation internet
An optimization based distributed algorithm for mobile data gathering in wireless sensor networks
INFOCOM'10 Proceedings of the 29th conference on Information communications
Joint mobile energy replenishment and data gathering in wireless rechargeable sensor networks
Proceedings of the 23rd International Teletraffic Congress
Distributed data gathering in multi-sink sensor networks with correlated sources
NETWORKING'06 Proceedings of the 5th international IFIP-TC6 conference on Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile and Wireless Communications Systems
A hybrid primal-dual algorithm with application to the dual transportation problems
ICCSA'05 Proceedings of the 2005 international conference on Computational Science and Its Applications - Volume Part IV
On embedding the volume algorithm in a variable target value method
Operations Research Letters
A Simple but Usually Fast Branch-and-Bound Algorithm for the Capacitated Facility Location Problem
INFORMS Journal on Computing
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Lagrangian duality is a frequently used technique for solving specially structured linear programs or for solving linear programming relaxations of nonconvex discrete or continuous problems within a branch-and-bound approach. In such cases, subgradient optimization methods provide a valuable tool for obtaining quick solutions to the Lagrangian dual problem. However, little is known or available for directly obtaining primal solutions via such a dual optimization process without resorting to penalty functions, or tangential approximation schemes, or the solution of auxiliary primal systems. This paper presents a class of procedures to recover primal solutions directly from the information generated in the process of using pure or deflected subgradient optimization methods to solve such Lagrangian dual formulations. Our class of procedure is shown to subsume two existing schemes of this type that have been proposed in the context of pure subgradient approaches under restricted step size strategies.