UTA method

The UTA method was originally proposed by E.Jacquet-Lagrèze and J.Siskos
in 1982. It has gained popularity thanks to implementation called PREFCALC,
written by E.Jacquet-Lagrèze. Then, it was improved and modified by several authors
(see the References at the end of the Manual).
UTA+ was written in Borland C++ 3.1 with Object Windows Library, at the
Poznan University of Technology, Poland.
The UTA+ software is the latest implementation of the UTA method in
Windows environment. It summarizes all important contributions made by other
authors and offers some new possibilities, in particular, a “compensation” of
marginal utility functions controlled by the user and the use of preference intensities
in addition to the ranking defined by the user.
The method can be used to solve the problems of multicriteria choice and
ranking on a set A of alternatives. It constructs an additive utility function nom a
preference weak order defined by the user on a subset A’ of reference alternatives.
The construction, based on a principle of ordinal regression, consists of solving a
small LP problem. The software proposes marginal utility functions in piecewise
linear form as compatible as possible with the given weak order. It allows the user to
modify interactively the marginal utility functions within limits following from a
sensitivity analysis of the ordinal regression problem. For these modifications, the
user is helped by a friendly graphical interface.
The utility function accepted by the user serves then to define a weak order on
the whole set A of alternatives.
The UTA+ software is composed of four main modules:
I – Problem editing, including definition of criteria and alternatives, and of the most
and least preferred values of criteria.
II – Definition of a ranking ( preference weak order ) on a small set of reference
III – Ordinal regression, including specification of required properties of the utility
function prior to application of the solution procedure.
IV – Display and modification of the marginal utility functions and application of the
accepted utility function for the calculation of the final ranking of alternatives

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