Simplex-like sequential methods for a class of generalized fractional programs

Riccardo Cambini (), Laura Carosi (), Laura Martein () and Ezat Valipour ()
Additional contact information
Riccardo Cambini: University of Pisa
Laura Carosi: University of Pisa
Laura Martein: University of Pisa
Ezat Valipour: Shahid Bahonar University of Kerman

Mathematical Methods of Operations Research, 2017, vol. 85, issue 1, No 6, 77-96

Abstract: Abstract A sequential method for a class of generalized fractional programming problems is proposed. The considered objective function is the ratio of powers of affine functions and the feasible region is a polyhedron, not necessarily bounded. Theoretical properties of the optimization problem are first established and the maximal domains of pseudoconcavity are characterized. When the objective function is pseudoconcave in the feasible region, the proposed algorithm takes advantage of the nice optimization properties of pseudoconcave functions; the particular structure of the objective function allows to provide a simplex-like algorithm even when the objective function is not pseudoconcave. Computational results validate the nice performance of the proposed algorithm.

Keywords: Generalized fractional programming; Pseudoconcavity; Sequential methods; Global optimization; 90C05; 90C31; 90C32; 26B25 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s00186-016-0556-y

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