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