This paper takes a fresh look at sensitivity analysis in linear programming. We propose a merged approach that brings together the insights of Wendell’s tolerance and Wagner’s global sensitivity approaches. The modeler/analyst is then capable of answering questions concerning stability, trend, model structure, and data prioritization simultaneously. Analytical as well as numerical aspects of the approach are discussed for separate as well as simultaneous variations in the objective function coefficients and right-hand side terms. A corresponding efficient numerical implementation procedure is proposed. A classical production problem illustrates the findings.

A global tolerance approach to sensitivity analysis in linear programming

Borgonovo, Emanuele
;
2018

Abstract

This paper takes a fresh look at sensitivity analysis in linear programming. We propose a merged approach that brings together the insights of Wendell’s tolerance and Wagner’s global sensitivity approaches. The modeler/analyst is then capable of answering questions concerning stability, trend, model structure, and data prioritization simultaneously. Analytical as well as numerical aspects of the approach are discussed for separate as well as simultaneous variations in the objective function coefficients and right-hand side terms. A corresponding efficient numerical implementation procedure is proposed. A classical production problem illustrates the findings.
2018
2017
Borgonovo, Emanuele; Buzzard, Greg; Wendell, Richard
File in questo prodotto:
File Dimensione Formato  
ISLP160621.pdf

non disponibili

Descrizione: Working paper prima del processo di revisione
Tipologia: Documento in Pre-print (Pre-print document)
Licenza: NON PUBBLICO - Accesso privato/ristretto
Dimensione 508.5 kB
Formato Adobe PDF
508.5 kB Adobe PDF   Visualizza/Apri
EJOR_2017_Richard.docx

non disponibili

Descrizione: lettera Accettazione
Tipologia: Allegato per valutazione Bocconi (Attachment for Bocconi evaluation)
Licenza: NON PUBBLICO - Accesso privato/ristretto
Dimensione 13.37 kB
Formato Microsoft Word XML
13.37 kB Microsoft Word XML   Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11565/4001124
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 15
  • ???jsp.display-item.citation.isi??? 11
social impact