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Fractional 0–1 programming: applications and algorithms

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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.

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Acknowledgements

The authors would like to thank the anonymous Associate Editor and two reviewers for their constructive and helpful comments. The research of Oleg Prokopyev was in part performed while visiting the National Research University Higher School of Economics (Nizhny Novgorod) and partially supported by Laboratory of Algorithms and Technologies for Network Analysis (LATNA).

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  1. Department of Industrial Engineering, University of Pittsburgh, Pittsburgh, PA, 15261, USA

    Juan S. Borrero, Colin Gillen & Oleg A. Prokopyev

  2. Laboratory of Algorithms and Technologies for Networks Analysis, National Research University Higher School of Economics, Nizhny Novgorod, Russia, 603093

    Oleg A. Prokopyev

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  1. Juan S. Borrero
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Borrero, J.S., Gillen, C. & Prokopyev, O.A. Fractional 0–1 programming: applications and algorithms. J Glob Optim 69, 255–282 (2017). https://doi.org/10.1007/s10898-016-0487-4

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