TY - JOUR
T1 - Pseudo-criteria versus linear utility function in stochastic multi-criteria acceptability analysis
AU - Lahdelma, Risto
AU - Salminen, Pekka
PY - 2002/9/1
Y1 - 2002/9/1
N2 - Stochastic multi-criteria acceptability analysis (SMAA) is a multi-criteria decision support method for multiple decision-makers (DMs) in discrete problems. SMAA does not require explicit or implicit preference information from the DMs. Instead, the method is based on exploring the weight space in order to describe the valuations that would make each alternative the preferred one. Partial preference information can be represented in the weight space analysis through weight distributions. In this paper we compare two variants of the SMAA method using randomly generated test problems with 2-12 criteria and 4-12 alternatives. In the original SMAA, a utility or value function models the DMs' preference structure, and the inaccuracy or uncertainty of the criteria is represented by probability distributions. In SMAA-3, ELECTRE III-type pseudo-criteria are used instead. Both methods compute for each alternative an acceptability index measuring the variety of different valuations that supports this alternative, and a central weight vector representing the typical valuations resulting in this decision. We seek answers to three questions: (1) how similar are the results provided by the decision models, (2) what kind of systematic differences exists between the models, and (3) how could one select indifference and preference thresholds of the pseudo-criteria model to match a utility model with given probability distributions?
AB - Stochastic multi-criteria acceptability analysis (SMAA) is a multi-criteria decision support method for multiple decision-makers (DMs) in discrete problems. SMAA does not require explicit or implicit preference information from the DMs. Instead, the method is based on exploring the weight space in order to describe the valuations that would make each alternative the preferred one. Partial preference information can be represented in the weight space analysis through weight distributions. In this paper we compare two variants of the SMAA method using randomly generated test problems with 2-12 criteria and 4-12 alternatives. In the original SMAA, a utility or value function models the DMs' preference structure, and the inaccuracy or uncertainty of the criteria is represented by probability distributions. In SMAA-3, ELECTRE III-type pseudo-criteria are used instead. Both methods compute for each alternative an acceptability index measuring the variety of different valuations that supports this alternative, and a central weight vector representing the typical valuations resulting in this decision. We seek answers to three questions: (1) how similar are the results provided by the decision models, (2) what kind of systematic differences exists between the models, and (3) how could one select indifference and preference thresholds of the pseudo-criteria model to match a utility model with given probability distributions?
KW - Decision support systems
KW - Decision theory
KW - Multiple criteria analysis
KW - Pseudo-criteria
KW - Utility theory
UR - http://www.scopus.com/inward/record.url?scp=0036722399&partnerID=8YFLogxK
U2 - 10.1016/S0377-2217(01)00276-4
DO - 10.1016/S0377-2217(01)00276-4
M3 - Article
AN - SCOPUS:0036722399
SN - 0377-2217
VL - 141
SP - 454
EP - 469
JO - European Journal of Operational Research
JF - European Journal of Operational Research
IS - 2
ER -