Fractional 0–1 programming: applications and algorithms

Juan S. Borrero (), Colin Gillen () and Oleg A. Prokopyev ()
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Juan S. Borrero: University of Pittsburgh
Colin Gillen: University of Pittsburgh
Oleg A. Prokopyev: University of Pittsburgh

Journal of Global Optimization, 2017, vol. 69, issue 1, No 11, 255-282

Abstract: Abstract We consider a class of nonlinear integer optimization problems commonly known as fractional 0–1 programming problems (also, often referred to as hyperbolic 0–1 programming problems), where the objective is to optimize the sum of ratios of affine functions subject to a set of linear constraints. Such problems arise in diverse applications across different fields, and have been the subject of study in a number of papers during the past few decades. In this survey we overview the literature on fractional 0–1 programs including their applications, related computational complexity issues and solution methods including exact, approximation and heuristic algorithms.

Keywords: Fractional 0–1 programming; Hyperbolic 0–1 programming; Nonlinear integer optimization; Binary optimization (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s10898-016-0487-4

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