The SIMUS Method
This chapter aims at explaining the SIMUS method, trying to show without formulas how it works. Its purpose is to illustrate the DM about its principles and characteristics for him/her to understand and apply it without going into complex mathematical demonstrations. That is, one thing is to understand a method and to know how to use it and how to get the most from it and another is to be knowledgeable about its mathematical intricacies.
SIMUS is a hybrid method based on linear programming, weighted sum and outranking methods.
If the reader is interested or perhaps rather curious about how LP works, in the Appendix is a detailed and accessible explanation. Since SIMUS is also grounded on the two above-mentioned techniques, it produces two results but with the same ranking. It is the equivalent of solving a problem with two distinctive methods and getting coincident rankings. Naturally, it does not mean that SIMUS delivers the ‘true’ solution, if it exists, but these two similar outputs offer a good deal of reliability. Although SIMUS is a heuristic method, the compromising solution obtained is based on the Pareto efficient matrix.
An application example illustrates how to load the data into the SIMUS software and shows its operation. The chapter continues explaining how to incorporate especial and real-world issues in the model and ends examining why both LP and SIMUS do not produce rank reversal.
- *Cox M (2015) Expected utility theory. Accessed 23 Sept 2017Google Scholar
- *Dantzig G (1948) Linear programming and extensions. United States Air ForceGoogle Scholar
- *Izishaka A, Nemery P (2013) Multicriteria decision software: methods and analysis. Wiley, ChichesterGoogle Scholar
- Kothari CR (2009) An introduction to operational research, 3rd edn. Vikas Publishing House PVT LTD. Noida, IndiaGoogle Scholar
- Lliso P, Munier N (2014) Multicriteria decision-making by simus. http://decisionmaking.esy.es/. Accessed 8 July 2018
- *Mareschal B, De Smet Y, Nemery N (2008) Rank reversal in Promethee II method. Some new results. International conference on industrial engineering and engineering management. p 2008. Solvay Business School, Universitè Livre de BruxellesGoogle Scholar
- *OECD programme, Dumanski J, Pier C. Application of the pressure-state-response framework for the land quality indicators (LQI) programme http://www.fao.org/docrep/W4745E/w4745e08.htm. Accessed 7 May 2018
- *Shing Y, Lee L, Chun S, Chung D (2013) A critical view of multi-criteria decision-making methodologies. Inf Syst 14(1):358–365Google Scholar
- *Solver – FrontLine Systems. http://www.solver.com/. Accessed 7 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 Multi Criteria Decis Anal 10(1):11–25. John Wiley and SonsGoogle Scholar
- *Verly C, De Smet Y (2013) Some considerations about rank reversal occurrences in the PROMETHEE methods. Int J Multicriteria Decis Mak. Part of Interseries on Operations Research Book Series (ISOR, volume 233)Google Scholar
- *Wang J-M, Luo Y (2009) On rank reversal in decision analysis. Math Comput Model 49(5–6):1221–1229Google Scholar
- *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 5 Dec 2015
- *Zopounides C, Pardalos P (2010) Handbook of multi criteria analysis. Springer. Springer-Verlag Berlin/HeidelbergGoogle Scholar