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On The Properties Of ∊-Sensitivity Analysis For Linear Programming

Author

Listed:
  • CHAN-KYOO PARK

    (Department of Management, Dongguk University, 3-26 Pil-dong, Jung-gu, Seoul 100-715, Korea)

  • WOO-JE KIM

    (Department of Industrial and Information Systems Engineering, Seoul National University of Technology, Seoul, 139-743, Korea)

  • SOONDAL PARK

    (Department of Industrial Engineering, Seoul National University, Seoul, 151-742, Korea)

Abstract

∊-Sensitivity analysis (∊-SA) is a kind of method to perform sensitivity analysis for linear programming. Its main advantage is that it can be directly applied for interior-point methods with a little computation. In this paper, we discuss the property of ∊-SA analysis and its relationship with other sensitivity analysis methods. First, we present a new property of ∊-SA, from which we derive a simplified formula for finding the characteristic region of ∊-SA. Next, based on the simplified formula, we show that the characteristic region of ∊-SA includes the characteristic region of Yildirim and Todd's method. Finally, we show that the characteristic region of ∊-SA asymptotically becomes a subset of the characteristic region of sensitivity analysis using optimal partition. Our results imply that ∊-SA can be used as a practical heuristic method for approximating the characteristic region of sensitivity analysis using optimal partition.

Suggested Citation

  • Chan-Kyoo Park & Woo-Je Kim & Soondal Park, 2005. "On The Properties Of ∊-Sensitivity Analysis For Linear Programming," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 22(02), pages 135-151.
    • Handle: RePEc:wsi:apjorx:v:22:y:2005:i:02:n:s0217595905000467
    DOI: 10.1142/S0217595905000467
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