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An Algorithm for Excluding Redundant Assessments in a Multiattribute Utility Problem
Author(s) -
Yerkin G. Abdildin,
Ali E. Abbas
Publication year - 2012
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2012.04.086
Subject(s) - computer science , independence (probability theory) , complement (music) , algorithm , mathematical optimization , set (abstract data type) , representation (politics) , expected utility hypothesis , function (biology) , task (project management) , mathematical economics , mathematics , statistics , biochemistry , chemistry , management , evolutionary biology , complementation , politics , biology , law , political science , programming language , economics , gene , phenotype
The construction of a multiattribute utility function (MUF) is a fundamental step in decision analysis and can be a difficult task to perform unless some decomposition of the utility function is performed. When partial utility independence conditions exist, the functional form is decomposed into a number of lower-order utility assessments. Often the functional form, resulting from such independence conditions, includes duplicate and redundant assessments. This paper introduces a twos-complement exclusion algorithm for determining the minimal set of utility assessments required for a MUF with partial utility independence. The algorithm uses a ternary matrix representation of utility assessments. A comparison with a “brute-force” approach is also provided

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