Abstract
It is possible to reduce human losses during the cargo delivery to units on the battlefield with the use of unmanned systems (UMSs), including logistical unmanned ground vehicles (UGV) of various groups carrying capacity and unmanned aircraft systems (UAS). The urgent task is to determine the required number of unmanned cargo delivery systems in the interests of the mechanized infantry battalion.
The method of determining the number of unmanned cargo delivery systems for the logistical means (LM) transportation to the units of the mechanized infantry battalion is described. The optimality criterion of the selected composition of the system is the maximum efficiency-cost ratio (ECR) under the condition of transporting the maximum weight of LM required for the battle day from the combat supply point to the units of the mechanized infantry battalion. In this case, the efficiency indicator is the share of the total weight of LM that must be delivered to the units. In order to calculate this indicator, it is necessary to estimate the probability of successful delivery of LM to different battalion units for each UMSs. The cost indicator is the product of the masses of the cargo and energy costs on the delivery route, purchase costs and total costs for operating the UMSs during the forecasted average life of operation in terms of 1 kg of cargo. Two transport tables are built based on the results of the calculations. The first table includes probability weighting factors, and the second includes weighting factors of the cost of delivering LM from a combat supply point to units by various UMSs. For each of these transport problems, the optimal solution is obtained by linear programming methods, and for the ECR, by methods of optimization of problems with a nonlinear objective function, which is illustrated by an example using the "Solver" add-on in the Excel spreadsheet processor.
Keywords: logistic support, unmanned systems, logistical unmanned ground vehicles, unmanned aircraft systems, load capacity, cargo delivery, efficiency-cost, optimization of an amount.
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