Application of objective criteria saturation to select best value alternative from fuzzy requirements

Abstract

This paper presents a modified Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for evaluating system concepts using minimum and maximum customer requirements to determine a best value alternative. The purpose of this decision analysis technique is to identify system alternatives with an optimal combination of performance, reliability, and cost based on ideal customer requirements. Currently, most conventional TOPSIS models use minimum and maximum values under a specific criterion to evaluate each alternative. Using these models, an alternative being evaluated could receive significantly higher scores when reported capabilities are greater than ideal customer requirements. This problem is pronounced whenever weights are applied to criteria where excessive capabilities are recorded. If an organizational goal is to select the best value alternative, use of conventional TOPSIS models may not lead to the best value decision. The modified TOPSIS method presented in this paper restricts scoring for alternatives that provide excess capabilities beyond ideal customer requirements. Criteria weights are assigned according to a customer's prioritized requirements. This Objective Criteria Saturation TOPSIS (OCS-TOPSIS) method was created to provide Decision Makers (DM) with a tool to evaluate system alternatives against performance criteria, reliability and life cycle costs. To demonstrate the effectiveness of OCS-TOPSIS, a basic example is provided that displays the cost savings outcome over traditional TOPSIS.