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

A life cycle costing (LCC) algorithm that can effectively deal with judgmental assessments of input parameters is proposed. This algorithm is based on the fuzzy set theory 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 subjective assessments. Three major issues were considered in the development of the algorithm. First, an appropriate mathematical framework for representing subjective imprecision was identified. Then, the original LCC closed-form equation was reformulated so that uncertainties in all input parameters can be modelled in an effective and convenient manner. Finally, the formulated model was implemented in the form of an efficient computational algorithm. The algorithm handles a number of alternatives with imprecise input data and ranks them automatically. The solution of a selected example problem is included to clarify the theory of the model

Towards effective consideration of non-financial factors in the design and management of construction assets.

The decisive role of non-financial factors in the design and management of construction assets is highlighted and existing techniques used to include these factors in the decision-making process are critically reviewed. An effective algorithm has been developed to include non-monetary benefits of competing design alternatives in whole-life costing studies. The unique feature of the algorithm, amongst others, is that it proceeds through logical steps that can be followed and assessed by decision-makers. Details of the computer implementation of the algorithm are presented. The solution of a selected example problem is also included to illustrate the theory of the algorithm