A fuzzy model and algorithm to handle subjectivity in life cycle costing based decision-making.

Abstract

A life cycle costing (LCC) algorithm that can effectively deal with judgmental
\nassessments of input parameters is proposed. This algorithm is based on the fuzzy set
\ntheory and interval mathematics. The development of the algorithm is motivated by the need to handle in a systematic and a more objective way the imprecision in these
\nsubjective assessments. Three major issues were considered in the development of the
\nalgorithm. First, an appropriate mathematical framework for representing subjective imprecision was identified. Then, the original LCC closed-form equation was
\nreformulated so that uncertainties in all input parameters can be modelled in an
\neffective and convenient manner. Finally, the formulated model was implemented in the
\nform of an efficient computational algorithm. The algorithm handles a number of
\nalternatives with imprecise input data and ranks them automatically. The solution of a
\nselected example problem is included to clarify the theory of the model.