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An exact method for a discrete multiobjective linear fractional optimization

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  • Chergui, M. E-A
  • Moulai, M.

Abstract

Integer linear fractional programming problem with multiple objective MOILFP is an important field of research and has not received as much attention as did multiple objective linear fractional programming. In this work, we develop a branch and cut algorithm based on continuous fractional optimization, for generating the whole integer efficient solutions of the MOILFP problem. The basic idea of the computation phase of the algorithm is to optimize one of the fractional objective functions, then generate an integer feasible solution. Using the reduced gradients of the objective functions, an efficient cut is built and a part of the feasible domain not containing efficient solutions is truncated by adding this cut. A sample problem is solved using this algorithm, and the main practical advantages of the algorithm are indicated.

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File URL: http://mpra.ub.uni-muenchen.de/12097/
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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 12097.

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Date of creation: 09 Jun 2007
Date of revision: 09 Jan 2008
Handle: RePEc:pra:mprapa:12097

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Keywords: multiobjective programming; integer programming; linear fractional programming; branch and cut;

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  1. Metev, Boyan & Gueorguieva, Dessislava, 2000. "A simple method for obtaining weakly efficient points in multiobjective linear fractional programming problems," European Journal of Operational Research, Elsevier, vol. 126(2), pages 386-390, October.
  2. Schaible, Siegfried, 1981. "Fractional programming: Applications and algorithms," European Journal of Operational Research, Elsevier, vol. 7(2), pages 111-120, June.
  3. Costa, Joao Paulo, 2007. "Computing non-dominated solutions in MOLFP," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1464-1475, September.
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Cited by:
  1. Zerdani, Ouiza & Moulai, Mustapha, 2011. "Optimization over an integer efficient set of a Multiple Objective Linear Fractional Problem," MPRA Paper 35579, University Library of Munich, Germany.

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