Multi-Criteria Optimization of Resource Management in Conditions of Uncertainty in Formalizing Initial Data Based on Standardized Approach

The article puts forward a modified algorithm of multi-criteria optimization of stock management in conditions of uncertainty based on using standardized data to present figures of particular criteria. The approach aims at elimination of inadequate choice phenomenon, when criteria with lower order of values can hardly affect the final solution due to misbalance in their numerical ranges. It was shown that transit to standardized data can help smooth the distorting effect of various scales of measurements and provide commensurability of each criterion contribution to the integral estimation of alternatives. In contrast to the earlier approach using generalized data the new modification shows comparable efficiency in elimination of inadequate choice phenomenon and provides another ranging of alternatives by widening a set of methods of multi-criteria analysis. Quantitative verification of algorithm was conducted by resolving the task of choosing logistic intermediary and strategy of product stock management in conditions of uncertainty in demand and delays in delivery. It was found out that the use of standardized data gives a chance in some cases to eliminate inadequate choice phenomenon. The research findings are important for developing corporate systems of decision-making support, which can ensure well-balanced account of multiple controversial criteria in conditions of uncertainty.