Tolerance Sensitivity and Optimality Bounds in Linear Programming

Richard E. Wendell ()
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Richard E. Wendell: Katz Graduate School of Business, University of Pittsburgh, Pittsburgh, Pennsylvania 15260

Management Science, 2004, vol. 50, issue 6, 797-803

Abstract: Traditional sensitivity analysis in linear programming usually focuses on variations of one coefficient or term at a time. The tolerance approach was proposed to provide a decision maker with an effective and easy-to-use method to summarize the effects of simultaneous and independent changes in selected parameters. In particular, for variations of the objective function coefficients, the approach gives a maximum-tolerance percentage within which selected coefficients may vary from their estimated values (within a priori limits) while still retaining the same optimal basic feasible solution. Although an optimal solution may cease being optimal for variations beyond the maximum-tolerance percentage, it may still be close to optimal. Herein we characterize the potential loss of optimality for variations beyond the maximum-tolerance percentage as a maximum-regret function. We consider theoretical properties of this function and propose a method to compute a relevant portion of it.

Keywords: sensitivity analysis; linear programming; optimality bounds (search for similar items in EconPapers)
Date: 2004
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Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:50:y:2004:i:6:p:797-803

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