WINPRE - Workbench for Interactive Preference Programming

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WINPRE - Workbench for Interactive Preference
Programming

• Raimo P. Hämäläinen
• Jyri Helenius
• http//www.hut.fi/Units/Systems.Analysis

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Interval MCDA methods

• PAIRS Preference Assessment by Incomplete Ratio
  Statements (Salo ,Hämäläinen
  OR 1992)
• SPAIRS Simple PAIRS
  Interval SMART/SWING (New method)
• Interval AHP-Preference programming
  (Salo,Hämäläinen MCDM 1991,EJOR 1995)

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Related Work

• Non-hierarchical models
• UTA (Jacquet-Lagreze Siskos 1982)
• Additive utility function estimated from
  regression analysis of ordinal preference
  statements
• HOPIE (Weber 1985)
• Constraints on additive or multiplicative utility
  function from value intervals and holistic
  judgements among hypothetical alternatives

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• ARIADNE
• Imprecision modelled by set inclusion holistic
  judgements among alternatives
• ISMAUT (White et al. 1984, Scherer et al. 1986)
• Uncertainty about attribute weights and
  utilities, exactly specified probabilities
• Hierarchical models
• RID (Moskowitz et al. 1989)
• Imprecise probabilities and utilities in decision
  trees
• MCRID (Moskowitz et al. 1991)
• imprecise attribute weights reduction of the set
  of non-dominated alternatives via stochastic
  dominance

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• AHP
• Saaty Vargas (1987)
• Interval valued replies to pairwise comparisons
  suggested as a way to capture subjective
  uncertainty direct analysis of interval matrices
  intractable
• Arbel (1989)
• Interval judgements interpreted as linear
  constraints on local priorities
• Salo Hämäläinen (1990)
• Efficient decomposition scheme for processing
  interval judgements in hierarchies

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PAIRS - Preference Assessment by Imprecise
Ratio Statements

• Interval value tree analysis
• Pairwise ratio statements about the relative
  importance of attributes ( as intervals)
• Value intervals for the alternative scores
  (imprecition in value function and measurements
  combined in WINPRE)
• Inconsistency in pairwise statements not allowed

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Dominance

• I Absolute a dominates b if lower bound of the
  value interval for a is higher than upper bound
  of the value interval for b.
• II Pairwise a dominates b if there are no
  feasible weights, so that V(b) gt V( a).
• I gt II , not II gt I

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SPAIRS Interval SMART/SWING

• Simple PAIRS local comparisons made with
  respect to one reference attribute only
• Generalization
• Reference most / least important or
  intermediate
• No inconsistency problems ( because there are no
  extra comparisons)
• Easier to use than other interval methods.

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Interval AHP

• Preference Programming term first used for AHP
  (Arbel 1988)
• Pairwise comparisons with upper and lower
  limits for criteria and alternatives
• Inconsistency not allowed
• not a version of true AHP
• consistency must in elicitation

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Preference programming

• DM gives preference statements, which define
  intervals of the weight ratios

• Value intervals for alternatives Series of LP
  - problems.

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The feasible region

• The attribute X is at least two but no more than
  four times as attractive as attribute Y

• Feasible region the set of local priority
  vectors which satisfy the inequalities arising
  from the interval judgements, i.e.

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Ambiguity Index

• Index, which characterizes how specific the DMs
  preference statements are

• Properties

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Advantages of interval methods

• Partial progressively increasing information
• Allows ambiquity -all comparisons not necessary
• Group decision support
• all opinions embedded into the interval

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WINPRE

• First to solve all interval methods
• Efficient algorithm computes extreme points
  instantaneously - sensitivity analysis
• Maximum number of subcriteria or alternatives is
  9
• Number of levels in the value tree not limited
• Results can be copied or linked to /from other
  Windows programs (e.g. Excel)

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Value ratings on attributes
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• SPAIRS with reference attribute in the middle

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• SPAIRS with reference attribute the most
  important SWING

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• Interval AHP pairwise comparison of attributes
  and alternatives

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• Export of results into Excel

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Future research

• Description of stuctured procedures based on
  interval method
• Behavioural testing with real cases and decision
  makers-individual and group
• Winpre software is a fully operational DSS tool
  available free for research purposes
• http//www.hut.fi/Units/Systems.Analysis

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References
The underlying methodology of the program is
described in the references below. PAIRS Salo
and R.P. Hämäläinen Preference assessment by
imprecise ratio statements, Operations Research,
Vol. 40, No. 6, November-December 1992, pp.
1053-1061. Preference Programming
(INPRE-mode) Salo and R.P. Hämäläinen Preference
programming through approximate ratio
comparisons, European Journal of Operational
Research, Vol. 82, Issue 3, 1995, pp.
458-475. Salo and R.P. Hämäläinen Processing
interval judgments in the analytic hierarchy
process, Proc. of the Ninth International
Conference Theory and Applications in Business,
Industry and Government, in Multipl Criteria
Decision Making, A. Goicocchea, L. Duckstein and
S. Zionts (eds.), Springer-Verlag, New-York,
August 1990, Fairfax, Virginia, 1991, pp.
359-371. Salo Inconsistency analysis by
approximately specified priorities, Mathematical
and Computer Modelling, Vol. 17, No. 4/5, 1993,
pp. 123-133.
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Related articles M. Pöyhönen and R.P. Hämäläinen
On the convergence of multiattribute weighting
methods, Helsinki University of Technology,
Systems Analysis Laboratory Research Reports A69,
October 1997. (Available from http//www.hut.fi/U
nits/Systems.Analysis/Publications/) M. Pöyhönen,
R.P. Hämäläinen and A. A. Salo An experiment on
the numerical modeling of verbal ratio
statements, Journal of Multi-Criteria Decision
Analysis, Vol. 6, 1997, pp. 1-10. Salo and R.P.
Hämäläinen PRIME - Preference ratios in
multiattribute evaluation, Helsinki University of
Technology, Systems Analysis Laboratory Research
Reports A43, July 1992. (revised December 1997)
(Available from http//www.hut.fi/Units/Systems.A
nalysis/Publications/) A. Salo and R.P.
Hämäläinen On the measurement of preferences in
the analytic hierarchy process, (and comments by
V. Belton, E. Choo, T. Donegan, T. Gear, T.
Saaty, B. Schoner, A. Stam, M. Weber, B. Wedley)
Journal of Multi-Criteria Decision Analysis, Vol.
6, 1997, pp. 309-339. A. Salo and R.P.
Hämäläinen Rejoinder The issue is understanding
the weights, Journal of Multi-Criteria Decision
Analysis, Vol. 6, 1997, pp. 340-343
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Applications, Group decisions See the references
below to get information about applications of
the PAIRS and Preference Programming methods. A.
Salo Interactive decision aiding for group
decision support, European Journal of Operational
Research, Vol. 84, 1995, pp. 134-149. R.P.
Hämäläinen and O. Leikola Spontaneous decision
conferencing in parliamentary negotiations, Proc.
of the 27th Hawaii International Conference on
Systems Sciences, IEEE Computer Society Press,
Hawaii, January 4-7, Vol. IV, 1995, pp.
290-299. R.P. Hämäläinen and O. Leikola
Spontaneous decision conferencing with top-level
politicians, OR Insight, Vol. 9, Issue 1, 1996,
pp. 24-28. R.P. Hämäläinen and M. Pöyhönen
On-line group decision support by preference
programming in traffic planning, Group Decision
and Negotiation, Vol. 5, 1996, pp. 485-500. R.P.
Hämäläinen, A. Salo and K. Pöysti Observation
about consensus seeking in a multiple criteria
environment, Proc. of the Twenty-Fifth Hawaii
International Conference on Systems Sciences,
Hawaii, Vol. IV, January 1992, pp. 190-198. R.P.
Hämäläinen and E. Kettunen On-line group
decision support by HIPRE 3 Group Link, Proc. of
the 3rd International Symposium on the Analytic
Hierarchy Process, Washington, D.C., July 11-13,
1994, pp. 547-557 A. Salo and R.P. Hämäläinen
Decision support under ambigous preference
statements, Proc. of the AIRO'90 Annual
conference of the Italian OR society, Sorrento,
Italy, October 1990, pp. 229-243