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Enhancing Multiattribute Evaluation with PRIME Preference Ratios

This document discusses the PRIME (Preference Ratios in Multiattribute Evaluation) model developed by Ahti A. Salo and Raimo P. Hämäläinen, focusing on its application in decision-making processes involving societal benefits, health, and economy. It compares various weighting methods, emphasizing tradeoffs and the theoretical foundations of ratio-based and SMART methods. The paper also tackles issues like incomplete information, decision criteria, dominance structures, and the impact of genetically modified organisms assessment. Additionally, it outlines elicitation processes for more effective decision-making, addressing uncertainties and providing comprehensive guidance.

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Enhancing Multiattribute Evaluation with PRIME Preference Ratios

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  1. PRIME - Preference Ratios in Multiattribute Evaluation Ahti A. Salo and Raimo P. Hämäläinen Systems Analysis Laboratory Helsinki University of Technology http://www.sal.hut.fi/ 7.9.1999

  2. Multiattribute weighting SOCIETAL BENEFIT Environment Health Economy Grant permit Deny permit

  3. Weighting methods • Tradeoff method • has a sound theoretical foundation • requires continuous measurement scales • may be rather difficult in practice • Ratio-based methods • very popular despite weaker theoretical foundation • SMART (Edwards 1977) • SMARTER (Edwards and Barron 1994) • AHP (Saaty 1980) • How to combine the advantages of both? • cf. preference measurement in the AHP (Salo and Hämäläinen 1997)

  4. Incomplete information • Complete information may be hard to acquire • alternatives and their impacts? • relative importance of attributes? • Examples • assessment of environmental impacts • cost of acquiring further information • partial stakeholder involvement • fluctuating preferences • What can be concluded on the basis of available information? • parametric uncertainties covered • structural uncertainties excluded

  5. Ratio comparisons • Estimates should not depend on the value representation • Ratios of value differences • not actionable as choices between naturally occurring options • axiomatizations by Dyer and Sarin (1979) and Vansnick (1984) • Direct rating an analogue • positioning on the range [0,100]

  6. Score elicitation • Estimates • Procedures • comparisons between pairs of adjacent levels • comparisons with regard to least preferred achievement level

  7. Weight elicitation • Estimates • Choice of alternatives • interval SMARTS - least and most preferred alternatives on each attribute • reference alternatives - any two alternatives • Choice of attributes • reference attributes - largest value difference • attribute sequencing - (rank) order attributes and compare adjacent ones

  8. Dominance structures • Absolute dominance • Pairwise dominance • Become increasingly conclusive

  9. Decision criteria (1) • Max-max • Max-min • Minimax regret

  10. Decision criteria (2) • Central values • Central weights • the same w.r.t. weights, assuming that scores are known • Provide guidance when decision rules do not hold • associated loss of value must be examined, however!

  11. Elicitation processes (1)

  12. Computational convergence • Questions • how effective are imprecise ratios? • which decision rules are best? • Randomly generated problems • 5,10,15 attributes; 5,10,15 alternatives • attribute weighting by interval SMART • error ratios 1.2, 1.5, 2 • 5000 problem instances

  13. Results • Central values minimise the expected loss of value • Few imprecise ratios improve performance in relation to ordinal information • As the number and precision of imprecise ratios increases • the number of nondominated alternatives declines • the expected loss of value decreases

  14. Genetically modified organisms • Technology assessment study for the Finnish Parliament • commissioned by the Futures Committee • delivered to the Speaker of the Parliament in September 1998 • debated in the plenary session in November 1998 • an extensive two-hour debate, commented on by two ministers • Precautionary Principle in Risk Management • commissioned by JRC/IPTS (ESTO network) • presented to the DG’s by the Forward Studies Unit in May 1999 • Problem characteristics • timely and highly controversial • large uncertainties • many concerns

  15. Value tree

  16. Ranges of weights

  17. Intermediate results

  18. Ranges of attribute weights

  19. Decision rules

  20. Conclusion • Characteristics • acknowledgement of uncertainties • maintenance of consistencies • alternative elicitation processes • guidance through decision rules • PRIME Decisions • full-fledged computer implementation • interactive decision support

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