A simple technique to improve linearized reformulations of fractional (hyperbolic) 0–1 programming problems

We consider reformulations of fractional (hyperbolic) 0–1 programming problems as equivalent mixed-integer linear programs (MILP). The key idea of the proposed technique is to exploit binary representations of certain linear combinations of the 0–1 decision variables. Consequently, under some mild c...

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Bibliographic Details
Published in:Operations research letters Vol. 44; no. 4; pp. 479 - 486
Main Authors: Borrero, Juan S., Gillen, Colin, Prokopyev, Oleg A.
Format: Journal Article
Language:English
Published: Elsevier B.V 01.07.2016
Subjects:
Binary representations
Equivalence
Fractional 0–1 programming
Hyperbolic 0–1 programming
Linear programming
Linearization
Mathematical models
Mixed integer linear programs
Operations research
Programming
Representations
Binary representations
Hyperbolic 0–1 programming
Fractional 0–1 programming
Mixed integer linear programs
Linearization
ISSN:0167-6377, 1872-7468
Online Access:Get full text
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Summary:We consider reformulations of fractional (hyperbolic) 0–1 programming problems as equivalent mixed-integer linear programs (MILP). The key idea of the proposed technique is to exploit binary representations of certain linear combinations of the 0–1 decision variables. Consequently, under some mild conditions, the number of product terms that need to be linearized can be greatly decreased. We perform numerical experiments comparing the proposed approach against the previous MILP reformulations used in the literature.
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ISSN:0167-6377
1872-7468
DOI:10.1016/j.orl.2016.03.015