Group prioritization in the AHP by fuzzy preference programming method

Abstract

In this paper we propose a new group fuzzy preference programming (GFPP) method for deriving group priorities from crisp pairwise comparison judgements, provided by multiple decision makers. The assessment of the group priorities is formulated as a fuzzy linear programming problem, maximizing the group's overall satisfaction with the group solution. The GFPP method combines the group synthesis and prioritization stages into a coherent integrated framework, which does not need additional aggregation procedures. The method can easily deal with missing judgements and provides a meaningful indicator for measuring the level of group satisfaction and group consistency. Scope and purpose The increasing complexity of decision-making problems in modern organizations requires the development of innovative decision support tools, which integrate theoretical methods of operations research and recent advancements of computing science. The main objective of this paper is to present a new approach for group decision making with the analytic hierarchy process (AHP), suitable for the development of group decision support systems. We focus on the problem of deriving local group priorities (weights of criteria and scores of alternatives), which is the most important stage of the AHP. The main characteristics of our method for prioritization and its possibilities for group decision-making support are illustrated through detailed examples.