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  • Data in many real-life engineering and economical problems suffer from inexactness. Herein we assume that we are given some intervals in which the data can simultaneously and independently perturb. We consider a generalized linear fractional programming problem with interval data and present an efficient method for computing the range of optimal values. The method reduces the problem to solving from two to four real-valued generalized linear fractional programs, which can be computed in polynomial time using an appropriate interior point method solver. We consider also the inverse problem: How much can data of a real generalized linear fractional program vary such that the optimal values do not exceed some prescribed bounds. We propose a method for calculating (often the largest possible) ranges of admissible variations; it needs to solve only two real-valued generalized linear fractional programs. We illustrate the approach on a simple von Neumann economic growth model.
  • Data in many real-life engineering and economical problems suffer from inexactness. Herein we assume that we are given some intervals in which the data can simultaneously and independently perturb. We consider a generalized linear fractional programming problem with interval data and present an efficient method for computing the range of optimal values. The method reduces the problem to solving from two to four real-valued generalized linear fractional programs, which can be computed in polynomial time using an appropriate interior point method solver. We consider also the inverse problem: How much can data of a real generalized linear fractional program vary such that the optimal values do not exceed some prescribed bounds. We propose a method for calculating (often the largest possible) ranges of admissible variations; it needs to solve only two real-valued generalized linear fractional programs. We illustrate the approach on a simple von Neumann economic growth model. (en)
Title
  • Generalized linear fractional programming under interval uncertainty
  • Generalized linear fractional programming under interval uncertainty (en)
skos:prefLabel
  • Generalized linear fractional programming under interval uncertainty
  • Generalized linear fractional programming under interval uncertainty (en)
skos:notation
  • RIV/00216208:11320/10:10028797!RIV11-MSM-11320___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • Z(MSM0021620838)
http://linked.open...iv/cisloPeriodika
  • 1
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 260338
http://linked.open...ai/riv/idVysledku
  • RIV/00216208:11320/10:10028797
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • generalized linear fractional programming; Interval analysis (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • NL - Nizozemsko
http://linked.open...ontrolniKodProRIV
  • [180B1C4A59E7]
http://linked.open...i/riv/nazevZdroje
  • European Journal of Operational Research
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 205
http://linked.open...iv/tvurceVysledku
  • Hladík, Milan
http://linked.open...ain/vavai/riv/wos
  • 000275363700004
http://linked.open...n/vavai/riv/zamer
issn
  • 0377-2217
number of pages
http://localhost/t...ganizacniJednotka
  • 11320
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