A Method for Structurally-Parametric Identification of a Multiple-Factor Estimation Function 

Tetyana43bestwebsmall.jpgTetyana Chaynikova is a graduate of the Kharkiv National University of Radioelectronics (KNURE), Ukraine and has recently passed her MPhil viva at WIT with a thesis on ‘A method for structurally-parametric identification of a multiple-factor estimation function’. The external examiner was Dr Charles Shoniregun from the University of East London and the internal examiner was Dr Alex Galybin.

In the thesis the problem of multifactor assessment and optimization is researched. The multifactor assessment and optimization are part of the complex and general problem of decision making. The complexity of the multifactor assessment problem solution is stipulated by dimensionality of the factorial space and dimension heterogeneity. An additional obstacle is created by the principal subjectivity of “the best solution” concept, where it is necessary to keep in mind decision-maker preferences.

The synthesis problem of the formal model for multifactor assessment is introduced. This model should conform to the specific decision-making situation. In turn it involves the solution of structural and parametric identification.

Principal concerns lie in the multi-attribute utility theory (MAUT) and in the selection of the utility function type.

The result of the research is preparation of a method and computational procedures based on structurally-parametric identification of an individual model for multiple-factor assessment.

The principal aspects of the developed method are:

  •     Development of the formal procedure for identification of the structure and quantitative parameters of the model of multiple-factor assessment for a set of alternative decisions.
  •     The use of a passive experiment for identification of results i.e. only the final results of a decision choice out of an admissible set of alternatives. It excludes the necessity of questioning and interviewing the decision-maker.


The results obtained can be applied to developing expert support systems in the field of marketing.

Further research is required in conversion of the individual model of multiple-factor assessment to the model of group assessment.

Tetyana presented an excellent thesis and as a result of her research both examiners recommended that she be awarded the degree of Master of Philosophy.

Grateful acknowledgement is given to the Foreign Office for their support.

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