Complexity of column generation in network design with path‐based survivability mechanisms

Abstract in Undetermined his survey deals with computational complexity of column generation problems arising in the design of survivable communication networks. Such problems are often modeled as linear programs based on noncompact multicommodity flow network formulations. These formulations involve an exponential number of path-flow variables, and therefore require column generation to be solved to optimality. We consider several path-based protection and restoration mechanisms and present results, both known and new, on the complexity of the corresponding column generation (also called pricing) problems. We discuss results for the case of single link or single node failures scenarios, and extend the considerations to multiple link failures. Further, we classify the design problems corresponding to different survivability mechanisms according to the structure of their pricing problem. Eventually, we show that almost all the encountered pricing problems are hard to solve for scenarios admitting multiple failures, while a great deal of them are NP-hard already for single failure scenarios. (Less)

[1]  Kazutaka Murakami Survivable network management for high-speed ATM networks , 1996 .

[2]  Refael Hassin,et al.  Approximation algorithms and hardness results for labeled connectivity problems , 2007, J. Comb. Optim..

[3]  Arie M. C. A. Koster,et al.  Demand-wise Shared Protection for Meshed Optical Networks , 2005, Journal of Network and Systems Management.

[4]  Geir Dahl,et al.  A Cutting Plane Algorithm for Multicommodity Survivable Network Design Problems , 1998, INFORMS J. Comput..

[5]  R. Wessäly Dimensioning Survivable Capacitated Networks , 2000 .

[6]  Jian-Qiang Hu,et al.  Diverse routing in optical mesh networks , 2003, IEEE Trans. Commun..

[7]  Jean François Maurras,et al.  Network synthesis under survivability constraints , 2004, 4OR.

[8]  Dritan Nace,et al.  Assigning spare capacities in mesh survivable networks , 2000, Telecommun. Syst..

[9]  Mateusz Zotkiewicz Robust routing optimization in resilient networks : Polyhedral model and complexity issues. (Optimisation robuste du routage dans les réseaux résilients : Modèle polyédrique et problèmes de complexité) , 2011 .

[10]  Mateusz Zotkiewicz,et al.  Complexity of resilient network optimisation , 2009, Eur. Trans. Telecommun..

[11]  J. W. Suurballe Disjoint paths in a network , 1974, Networks.

[12]  Richard M. Karp,et al.  On Linear Characterizations of Combinatorial Optimization Problems , 1982, SIAM J. Comput..

[13]  Martin Grötschel,et al.  The ellipsoid method and its consequences in combinatorial optimization , 1981, Comb..

[14]  M. Dzida,et al.  Path Generation for a Class of Survivable Network Design Problems , 2008, 2008 Next Generation Internet Networks.

[15]  Hervé Rivano,et al.  Shared Risk Resource Group Complexity and Approximability Issues , 2007, Parallel Process. Lett..

[16]  Angela Chiu,et al.  Issues for routing in the optical layer , 2001, IEEE Commun. Mag..

[17]  Cynthia Barnhart,et al.  Using Branch-and-Price-and-Cut to Solve Origin-Destination Integer Multicommodity Flow Problems , 2000, Oper. Res..

[18]  Stefan Irnich,et al.  Shortest Path Problems with Resource Constraints , 2005 .

[19]  Sebastian Orlowski,et al.  Local and global restoration of node and link failures in telecommunication networks , 2003 .

[20]  Laurence A. Wolsey,et al.  Integer and Combinatorial Optimization , 1988, Wiley interscience series in discrete mathematics and optimization.

[21]  A. Dutta-Roy An overview of cable modem technology and market perspectives , 2001 .

[22]  Kazutaka Murakami,et al.  Optimal capacity and flow assignment for self-healing ATM networks based on line and end-to-end restoration , 1998, TNET.