BeCoMe: Easy-to-implement optimized method for best-compromise group decision making: Flood-prevention and COVID-19 case studies. (February 2021) - Vrana, Ivan; Tyrychtr, Jan; Pelikán, Martin
Abstract: Vrana et al. (2012a) presented the maximum-agreement-mean (MaxAgM) method, which aggregates expert opinions while focusing on points of agreement. Although MaxAgM can minimize Shannon entropy to optimize results, it has a high level of computational and conceptual complexity, yields difficult-to-interpret results, has no indicator of accuracy, and requires specialized software that is not widely available. In this paper, we present the best-compromise-mean (BeCoMe) method as a modified MaxAgM method. BeCoMe preserves the advantages of MaxAgM, but overcomes its limitations. To enable direct comparison, we applied the BeCoMe method to the same flood-prevention case study that was used to validate the original MaxAgM method. BeCoMe is a universal method, as it can be applied to evaluate environmental and educational measures, about pandemics, industries and resource issues. Here, we demonstrate the applicability of BeCoMe in real-life COVID-19 case study decisions which needed to be rapidly and efficiently made by the Czech government. Highlights: We apply an improved method for flood-prevention and COVID-19 case studies. The method eliminates the drawbacks of MaxAgM while performing similarly. We present an efficient method to solve COVID-19 decision-making as well as environmental problems.