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A least-squares minimum-cost network flow algorithm

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Abstract

Node-arc incidence matrices in network flow problems exhibit several special least-squares properties. We show how these properties can be leveraged in a least-squares primal-dual algorithm for solving minimum-cost network flow problems quickly. Computational results show that the performance of an upper-bounded version of the least-squares minimum-cost network flow algorithm with a special dual update operation is comparable to CPLEX Network and Dual Optimizers for solving a wide range of minimum-cost network flow problems.

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Author notes

  1. Seunghyun Kong

    Present address: , 438 Golden Harvest Loop, Cary, NC, 27519, USA

Authors and Affiliations

  1. SAS Institute Inc, 100 SAS Campus Drive, Cary, NC, 27513, USA

    Balaji Gopalakrishnan

  2. H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, 765 Ferst Drive, NW, Atlanta, GA, 30332-0205, USA

    Seunghyun Kong, Ellis L. Johnson & Joel S. Sokol

  3. School of Computer, Mathematical and Natural Science, Morgan State University, 1700 East Cold Spring Lane, Baltimore, MD, 21251, USA

    Earl Barnes

Authors
  1. Balaji Gopalakrishnan
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  2. Seunghyun Kong
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  3. Earl Barnes
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  4. Ellis L. Johnson
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  5. Joel S. Sokol
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Correspondence to Seunghyun Kong.

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Gopalakrishnan, B., Kong, S., Barnes, E. et al. A least-squares minimum-cost network flow algorithm. Ann Oper Res 186, 119–140 (2011). https://doi.org/10.1007/s10479-011-0858-7

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  • DOI: https://doi.org/10.1007/s10479-011-0858-7

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