Application of Global Line-Search in the Optimization of Networks

  • Jonas Mockus
  • William Eddy
  • Audris Mockus
  • Linas Mockus
  • Gintaras Reklaitis
Part of the Nonconvex Optimization and Its Applications book series (NOIA, volume 17)

Abstract

An application of Global Line-Search (GLS) to the optimization of networks is considered in this chapter. Advantages and disadvantages are discussed. It is shown that GLS provides the global minimum after a finite number of steps in two cases of piecewise linear cost functions of arcs. The first case is, where all cost functions are convex. The second case is, where all costs are equal to zero at zero flow, and equal to some constant at non-zero flow. In other cases the global line-search approaches the global minimum with a small average error. Therefore this algorithm is regarded as a good heuristics.

Keywords

Cost Function Global Minimum Good Heuristic Power Transmission Line Zero Flow 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 1997

Authors and Affiliations

  • Jonas Mockus
    • 1
    • 2
    • 3
  • William Eddy
    • 4
  • Audris Mockus
    • 5
  • Linas Mockus
    • 6
  • Gintaras Reklaitis
    • 6
  1. 1.Institute of Mathematics and InformaticsKaunas Technological UniversityVilniusLithuania
  2. 2.Vytautas Magnus UniversityVilniusLithuania
  3. 3.Vilnius Technical UniversityVilniusLithuania
  4. 4.Department of StatisticsCarnegie-Mellon UniversityPittsburghUSA
  5. 5.Lucent Technologies AT&T Bell LaboratoriesPittsburghUSA
  6. 6.School of Chemical EngineeringPurdue UniversityW. LafayetteUSA

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