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An Algorithm for Solving Interval Linear Programming Problems

Author

Listed:
  • A. Charnes

    (University of Texas, Austin, Texas)

  • Frieda Granot

    (University of British Columbia, Vancouver, British Columbia)

  • F. Phillips

    (University of Texas, Austin, Texas)

Abstract

This paper presents an algorithm for solving interval linear programming (IP) problems. The algorithm is a finite iterative method. At each iteration it solves a full row rank, (IP) problem with only one additional constraint.

Suggested Citation

  • A. Charnes & Frieda Granot & F. Phillips, 1977. "An Algorithm for Solving Interval Linear Programming Problems," Operations Research, INFORMS, vol. 25(4), pages 688-695, August.
    • Handle: RePEc:inm:oropre:v:25:y:1977:i:4:p:688-695
    DOI: 10.1287/opre.25.4.688
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    Cited by:

    1. Savin Treanţă & Omar Mutab Alsalami, 2024. "On a Weighting Technique for Multiple Cost Optimization Problems with Interval Values," Mathematics, MDPI, vol. 12(15), pages 1-10, July.
    2. Figueroa–García, Juan Carlos & Hernández, Germán & Franco, Carlos, 2022. "A review on history, trends and perspectives of fuzzy linear programming," Operations Research Perspectives, Elsevier, vol. 9(C).
    3. Yating Guo & Guoju Ye & Wei Liu & Dafang Zhao & Savin Treanţǎ, 2021. "Optimality Conditions and Duality for a Class of Generalized Convex Interval-Valued Optimization Problems," Mathematics, MDPI, vol. 9(22), pages 1-14, November.
    4. Wu, Hsien-Chung, 2009. "The Karush-Kuhn-Tucker optimality conditions in multiobjective programming problems with interval-valued objective functions," European Journal of Operational Research, Elsevier, vol. 196(1), pages 49-60, July.

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