ENBIS: European Network for Business and Industrial Statistics

Multicriteria optimization using R and the desirability package desire

23 September 2009, 10:05 – 10:25

Abstract

Submitted by

Olaf Mersmann

Authors

Olaf Mersmann Heike Trautmann Detlef Steuer Claus Weihs Uwe Ligges

Affiliation

Fakultät Statistik, Technische Universität Dortmund Fakultät WiSo, Helmut-Schmidt Universität Hamburg

Abstract

Desirability functions and desirability indices are powerful tools for
multicriteria optimization und multicriteria quality control
purposes. The package desire not only provides functions for computing
desirability functions of Harrington- and Derringer/Suich-type but
also allows the specification of functions in an interactive
manner. Density and distribution functions of the desirability
functions and the desirability index are integrated including the
possibility of random number generation, . Optimization procedures for
the desirability index and a method for determining the uncertainty of
the optimum influence factor levels as wells as a control chart for
the desirability index with analysis of out-of control-signals are
implemented. The Desirability Pareto-Concept allows focussing on
relevant parts of the Pareto-front by integrating
a-priori-expert-knowledge in the multicriteria optimization process.

We will focus on the practical aspects of optimizing. First we will
give a short review of the traditional optimization strategy using
desirability indices. Then we will show an example of the procedure
using data from a chocolate production process and extend it by
including the variance of the estimates in the optimization.

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