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Extensions of Pareto efficiency analysis to integer goal programming

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  • Tamiz, M.
  • Mirrazavi, S. K.
  • Jones, D. F.

Abstract

This paper focuses on the design, development and implementation of new Pareto efficiency detection and restoration techniques for integer goal programming. The design of the algorithms and their implementation issues within (an otherwise continuous) goal programming system are detailed. The differences between continuous and integer goal programming regarding Pareto efficiency detection and restoration analysis are described. The integer Pareto efficiency techniques have been applied to a selection of problems from different industrial contexts in order to assess their computational performance. Finally, Pareto restoration and detection techniques are applied to an integer goal programming problem to illustrate the methodology.

Suggested Citation

  • Tamiz, M. & Mirrazavi, S. K. & Jones, D. F., 1999. "Extensions of Pareto efficiency analysis to integer goal programming," Omega, Elsevier, vol. 27(2), pages 179-188, April.
    • Handle: RePEc:eee:jomega:v:27:y:1999:i:2:p:179-188
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    References listed on IDEAS

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    1. A. Charnes & W. W. Cooper & R. O. Ferguson, 1955. "Optimal Estimation of Executive Compensation by Linear Programming," Management Science, INFORMS, vol. 1(2), pages 138-151, January.
    2. Jones, D. F. & Tamiz, M., 1995. "Expanding the flexibility of goal programming via preference modelling techniques," Omega, Elsevier, vol. 23(1), pages 41-48, February.
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    Cited by:

    1. X Li & P Beullens & D Jones & M Tamiz, 2009. "An integrated queuing and multi-objective bed allocation model with application to a hospital in China," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(3), pages 330-338, March.
    2. Mirrazavi, S. Keyvan & Jones, Dylan F. & Tamiz, M., 2001. "A comparison of genetic and conventional methods for the solution of integer goal programmes," European Journal of Operational Research, Elsevier, vol. 132(3), pages 594-602, August.
    3. Pati, Rupesh Kumar & Vrat, Prem & Kumar, Pradeep, 2008. "A goal programming model for paper recycling system," Omega, Elsevier, vol. 36(3), pages 405-417, June.
    4. Aouni, Belaid & Kettani, Ossama, 2001. "Goal programming model: A glorious history and a promising future," European Journal of Operational Research, Elsevier, vol. 133(2), pages 225-231, January.
    5. Ana Batista & Jorge Vera & David Pozo, 2020. "Multi-objective admission planning problem: a two-stage stochastic approach," Health Care Management Science, Springer, vol. 23(1), pages 51-65, March.
    6. S K Mirrazavi & S J Mardle & M Tamiz, 2003. "A two-phase multiple objective approach to university timetabling utilising optimisation and evolutionary solution methodologies," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(11), pages 1155-1166, November.
    7. M Larbani & B Aouni, 2011. "A new approach for generating efficient solutions within the goal programming model," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(1), pages 175-182, January.
    8. Padilla Garrido, Nuria & Guerrero Casas, Flor María, 2005. "La selección de carteras mediante programación por metas lexicográficas entera: una aplicación al mercado continuo español/Integer lexicographic goal programming for portfolio selection: an applicatio," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 23, pages 167-185, Abril.

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