Journal of Optimization Theory and Applications

, Volume 68, Issue 1, pp 95–116

Fractional programming by lower subdifferentiability techniques

  • M. Boncompte
  • J. E. Martínez-Legaz
Contributed Papers

DOI: 10.1007/BF00939937

Cite this article as:
Boncompte, M. & Martínez-Legaz, J.E. J Optim Theory Appl (1991) 68: 95. doi:10.1007/BF00939937

Abstract

The notion of lower subdifferentiability is applied to the analysis of convex fractional programming problems. In particular, duality results and optimality conditions are presented, and the applicability of a cutting-plane algorithm using lower subgradients is discussed. These methods are useful also in generalized fractional programming, where, in the linear case, the performance of the cutting-plane algorithm is compared with that of the most efficient version of the Dinkelbach method, which is based on the solution of a parametric linear programming problem.

Key Words

Fractional programming lower subdifferentiable functions duality optimality conditions cutting planes 

Copyright information

© Plenum Publishing Corporation 1991

Authors and Affiliations

  • M. Boncompte
    • 1
  • J. E. Martínez-Legaz
    • 2
  1. 1.Departamento de Matemática Económica, Financiera y ActuarialUniversidad de BarcelonaBarcelonaSpain
  2. 2.Departamento de Matemática Aplicada y AnálisisUniversidad de BarcelonaBarcelonaSpain

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