BeCoMe: Easy-to-implement optimized method for best-compromise group decision making: Flood-prevention and COVID-19 case studies. (February 2021)

• Record Type: Journal Article
• Authors: Vrana, Ivan; Tyrychtr, Jan; Pelikán, Martin
• Is Part Of: Environmental modelling & software. Volume 136(2021)
• Publication Date: 2021-02
• Subjects: Agreement -- Averaging operator -- Environmental decision making -- Multi-expert decisions -- Best-compromise result -- COVID-19; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2020.104953
• Languages: English
• ISSNs: 1364-8152

Abstract

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.