Fast optimization algorithms for large-scale mixed-integer linear fractional programming problems

Jiyao Gao, Fengqi You

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

We present three tailored algorithms for solving large-scale mixed-integer linear fractional programming (MILFP) problems. The first one combines Branch-and-Bound method with Charnes-Cooper transformation. The other two tailored MILFP solution methods are the parametric algorithm and the reformulation-linearization algorithm. Extensive computational studies are performed to demonstrate the efficiency of these algorithms and to compare them with some general-purpose mixed-integer nonlinear programming methods. A performance profile is given based on the algorithm performance analysis and benchmarking methods. The applications of these algorithms are further illustrated through an application on water supply chain optimization for shale gas production. Computational results show that the parametric algorithm and the reformulation-linearization algorithm have the highest efficiency among all the tested solution methods.

Original languageEnglish (US)
Title of host publicationACC 2015 - 2015 American Control Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5901-5906
Number of pages6
Volume2015-July
ISBN (Electronic)9781479986842
DOIs
StatePublished - Jan 1 2015
Event2015 American Control Conference, ACC 2015 - Chicago, United States
Duration: Jul 1 2015Jul 3 2015

Other

Other2015 American Control Conference, ACC 2015
CountryUnited States
CityChicago
Period7/1/157/3/15

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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