Integration of Data Envelopment Analysis-Based Preference Aggregation Method and α Particle Swarm Optimization Technique into Group Decision Model

Abstract

The design of sustainable infrastructure is a complex process because it involves various fields of expertise such as engineering, economy, environment, social, etc. To make sure experts from various fields are part of decision-making, a heterogeneous group is typically formed and the individual decisions of the group are combined simply by using an arithmetic mean, geometric mean, or by altering individual decisions to meet group consensus to generate a group decision. The drawbacks with these methods are inconsistency, dissatisfaction, and delayed decision process. This study proposes to use the Data Envelopment Analysis (DEA)-based preference aggregation method (commonly used by the business community) to combine the individual inputs into a group decision in conjunction with α constrained particle swarm optimization technique to generate consistent results in minimal time without altering individual decision-maker inputs. The proposed approach was evaluated by computing group decision weights for selection of a contractor out of six contractors with the help of nine decision-makers based on eight criteria using the analytic hierarchy process (AHP). The results indicated that the proposed method was able to identify the most suitable contractor in minimal time without human intervention.