Fractional 0–1 programming: applications and algorithms

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...

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Published inJournal of global optimization Vol. 69; no. 1; pp. 255 - 282
Main Authors Borrero, Juan S., Gillen, Colin, Prokopyev, Oleg A.
Format Journal Article
LanguageEnglish
Published New York Springer US 01.09.2017
Springer
Springer Nature B.V
Subjects
Algorithms
Applications programs
Approximation
Computer Science
Heuristic methods
Mathematics
Mathematics and Statistics
Operations Research/Decision Theory
Optimization
Programming
Real Functions
Surveys
Hyperbolic 0–1 programming
Fractional 0–1 programming
Binary optimization
Nonlinear integer optimization
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ISSN0925-5001
1573-2916
DOI10.1007/s10898-016-0487-4

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Summary: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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ISSN:0925-5001
1573-2916
DOI:10.1007/s10898-016-0487-4