Providing sufficient strict individual rankings' consistency level while group decision-making with feedback

Purpose – The paper's aim is to design and describe a new mathematical ware instrument allowing to facilitate group decision-making process with feedback. Design/methodology/approach – The aim is achieved through the development of a method for achieving sufficient consistency of individual expert alternative rankings based on evolutionary algorithms. The method is targeted at minimizing the number of times the experts in the group are addressed. Findings – The method developed and described in the paper allows to provide sufficient consistency level of individual expert rankings allowing to aggregate the rankings into a transitive preference relation. Research limitations/implications – The method is targeted at small expert groups. The method is limited by psycho-physiological constraints of human (expert's) mind, which is unable to analyze more than seven objects simultaneously. Practical implications – The method can be used in different scopes of human activity requiring ordinal expert estimation. Originality/value – The method is based on an original approach to organising feedback with experts. Genetic algorithm is used to determine the optimal candidate among the experts to be addressed at every feedback step.