A Consensus-Based Best-Worst Method for Multi-criteria Group Decision-Making

The resolution of Multi-criteria Decision-Making (MCDM) problems driven by human knowledge involves collecting their opinions, which usually implies the emergence of inconsistencies. The Best-Worst Method (BWM) was proposed to reduce such inconsistencies and, consequently, obtain more reliable solutions for MCDM problems. Classically, the BWM finds the optimal weights for a set of criteria from the preferences of only one stakeholder, but lately it has been extended to deal with multi-criteria group decision-making (MCGDM) problems. However, when several Decision-Makers (DMs) take part in a decision process, disagreements may appear among them. If these conflicts are neglected, experts may feel unsatisfied with the solution chosen by the group or even question the decision process. Therefore, this contribution proposes an extension of the BWM to smooth disagreements and obtain consensual solutions in MCGDM problems. To do so, an optimization model is introduced which derives a collectively agreed solution for the criteria weights. Additionally, such an optimization model is based on linear programming, which provides accurate results and the ability to deal with hundreds or thousands of DMs.