Optimization of inventory management strategies for order deliveries using multicriteria decision making under conditions of uncertainty

In today's inventory management, there is a need to optimize new models in order to select the best solution to ensure order fulfillment. These models must take into account various uncertainties, as well as the concept of time value of money. At the same time, it is important to note that in practice, appropriate solutions are often multicriteria due to the complex nature of supply chains.
To address this, the authors have developed a method for optimizing such tasks based on a combination of multicriteria optimization procedures and decision making under uncertainty. However, this approach is shown to require further refinement in practice. The proposed refinement aims to assist managers in avoiding undesirable outcomes related to alternative selection. These are situations related to phenomena that lead to the selection of alternatives that may not be optimal for the preferences of the decision maker.
The corresponding adjustment would result in introduction of a specific feature in the form of optimization procedures. In such an adjustment, it is proposed to present initial indicators of given specific criteria on the basis of so-called aggregated data, which eliminates the factor of dimensionality. A numerical example is provided using the development of a stock management strategy as an example, considering the need to select a logistics intermediary and in conditions of uncertainty regarding demand and potential delays in delivery. In this scenario, a weighted average of estimates of specific criteria is used as the selection criterion and the Hurwitz criterion is employed to account for uncertainty. Tab. 7, bibliogr. 20.