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A New Algorithm for Generalized Franctional Programs

Author

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  • Frenck, B.A.
  • Schaible, J.B.
  • Zhang, S.

Abstract

A dual problem for convex generalized fractional programs with no duality gap is presented and it is shown how this dual program can be efficiently solved using a parametric approach. The resulting algorithm can be seen as "dual" to the Dinkelbach-type algorithm for generalized fractional programs since it approximates the optimal objective value of the dual (primal) problem from below. Convergence results for this algorithm are derived and easy condition to achieve superlinear convergence is also established. Moreover, under some additional assumptions the algorithm also recovers at the same time an optimal solution of the primal problem. We also consider a variant of this new algorithm, based on scaling the dual parametric function.

Suggested Citation

  • Frenck, B.A. & Schaible, J.B. & Zhang, S., 1996. "A New Algorithm for Generalized Franctional Programs," The A. Gary Anderson Graduate School of Management 96-02, The A. Gary Anderson Graduate School of Management. University of California Riverside.
    • Handle: RePEc:fth:caland:96-02
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    Keywords

    PROGRAMMING ; MATHEMATICS;

    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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