Abstract
This chapter addresses a fundamental subject: sensitivity analysis. It is not only a checking procedure but also a tool that allows the DM to answer questions from stakeholders as well as a way to study different attitudes; without it a MCDM process is incomplete. The main reason for its use lies in the uncertainty of data, and therefore, a test must be performed to verify how a solution holds when certain parameters change.
In this book, sensitivity analysis is performed in a different and novel way, compared as it is done nowadays because there are nonsubjective assumptions, and it is based on what is believed to be a more rational approach, by using economics principles such as criteria marginal values instead of subjective criteria weights. The advantage over the lack of effectiveness and transparency of the actual procedure is that it permits not only determining when a ranking changes – as is the information given by all methods – but also getting a quantitative measure on the effect of these changes. It also provides a graphic display of how the objective value increases or decreases according to increments or decrements in some criteria.
Another advantage is that it allows analysis of how exogenous factors, related somehow with criteria, may affect the best selection in the future, during operation of the alternative selected. Due to this, it is possible to compute the value of diverse risks related to the potential changes of these exogenous factors.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
These references correspond to the authors mentioned in the text. However, there are also publications than are not mentioned in the text but that have been added for the reader to access more information about this chapter; they are identified with (*).
References
These references correspond to the authors mentioned in the text. However, there are also publications than are not mentioned in the text but that have been added for the reader to access more information about this chapter; they are identified with (*).
*Belton V, Gear T (1983) On a shortcoming of Saaty’s method of analytic hierarchies. Omega 11:228–230
*Cox M (2015) Expected utility theory. Accessed: 23 Sept 2017
*Dantzig G (1948) Linear programming and extensions. United States Air Force, Washington, DC
Gomory RE (1958) Outline of an algorithm for integer solutions to linear programs. Bull Am Math Soc 64(5):275–278 https://projecteuclid.org/euclid.bams/1183522679
*Ishizaka A, Nemery P (2013) Multicriteria decision software: methods and analysis. Wiley, Chichester
*Kantorovich L (1939) The best uses of economic resources. Pergamon Press (1965)
*Kothari C (2009) An introduction to operational research, 3rd edn. Vikas Publishing House PVT LTD Noida, India
*Lliso P, Munier N (2014) Multicriteria decision-making by Simus. http://decisionmaking.esy.es/. Accessed: 08 Dec 2017
*Mareschal B, De Smet Y, Nemery N (2008) Rank reversal in Promethee II method. Some new results. In: International Conference on Industrial Engineering and Engineering Management (2008). p. 2008
*Munier N (2011) A strategy for using multicriteria analysis in decision-making – a guide for simple and complex environmental projects. Springer, Dordrecht
PMI (Project Management Institute) (2017) A guide to the project management body of knowledge. https://www.bing.com/search?q=project+management+institute+a+guide+to+the+project+management&qs=n&form=QBRE&sp=1&pq=project+management+institute+a+guide+to+the+project+management&sc=0-62&sk=&cvid=0AE19844C0524098AFDD4D4E88CE1C57
*Saaty T, Sagir M (2009) An essay on rank preservation and reversal. Math Comput Model 49:1230–1243
*Shing Y, Lee L, Chun S, Chung D (2013) A critical view of multi-criteria decision-making methodologies. Issues Inf Syst 14(1):358–365
*Solver – FrontLine Systems. http://www.solver.com/. Accessed 08 Dec 2017
*Triantaphyllou E (2001) Two cases of rank reversal when the AHP and some of its additive variants are used that do not occur with the multiplicative AHP. J Multicrit Decis Anal 10(1):11–25. John Wiley and Sons
*Verly C, De Smet Y (2013) Some considerations about rank reversal occurrences in the PROMETHEE methods. Accepted for publication in the Int J Multicrit Decis Mak 71, 3(4):325–345
*Wan J-M, Luo Y (2009) On rank reversal in decision analysis. Math Comput Model 49(5–6):1221–1229
*Wang Y-M, Elhag T (2006) An approach to avoiding rank reversal in AHP – Elsevier. Decis Support Syst 42(3):1474–1480
*Wang X, Triantaphyllou E (2008) Ranking irregularities when evaluating alternatives by using some ELECTRE methods. Elsevier – Science Direct. Omega 36:45–63
*Zavadskas E, Antuvichevicene J, Saparauskas J, Turskis Z (2012) MCDM methods Waspas and Multimoora: verification of robustness of methods when assessing alternative solutions. http://www.ecocyb.ase.ro/20132/Zavadskas%20(T).pdf. Accessed 05 Dec 2015
*Zopounides C, Pardalos P (2010) Handbook of multi criteria analysis. Springer, Berlin/Heidelberg
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Munier, N., Hontoria, E., Jiménez-Sáez, F. (2019). Sensitivity Analysis by SIMUS: The IOSA Procedure. In: Strategic Approach in Multi-Criteria Decision Making. International Series in Operations Research & Management Science, vol 275. Springer, Cham. https://doi.org/10.1007/978-3-030-02726-1_8
Download citation
DOI: https://doi.org/10.1007/978-3-030-02726-1_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-02725-4
Online ISBN: 978-3-030-02726-1
eBook Packages: Business and ManagementBusiness and Management (R0)