## 4 Results
### Analysis of the Needs of Service Centers for Spare Parts
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{5}{c}{**Required Number of Starters and Winnings by Strategies**} \\ \hline  & \(\mathbf{P_{j}}\) & \(\mathbf{P_{1}}\) & \(\mathbf{P_{2}}\) & \(\mathbf{P_{3}}\) & \(\mathbf{P_{4}}\) & \(\mathbf{P_{5}}\) \\ \hline  & \(\mathbf{n_{j}}\) & & \(\mathbf{5}\) & \(\mathbf{15}\) & \(\mathbf{25}\) & \(\mathbf{35}\) & \(\mathbf{45}\) \\ \hline  & A\({}_{\text{i}}\) & \(\mathbf{n_{i}}\) & & & & \\ \cline{2-7} Number of & A\({}_{1}\) & \(5\) & \(91\),\(250\) & \(-172\),\(750\) & \(-436\),\(750\) & \(-700\),\(750\) & \(-964\),\(750\) \\ \cline{2-7}  & A\({}_{2}\) & \(15\) & \(73\),\(000\) & \(273\),\(750\) & \(9750\) & \(-254\),\(250\) & \(-518\),\(250\) \\ \cline{2-7}  & A\({}_{3}\) & \(25\) & \(54\),\(750\) & \(255\),\(500\) & \(456\),\(250\) & \(192\),\(250\) & \(-71\),\(750\) \\ \cline{2-7} strategy & A\({}_{4}\) & \(35\) & \(36\),\(500\) & \(237\),\(250\) & \(438\),\(000\) & \(638\),\(750\) & \(374\),\(750\) \\ \cline{2-7}  & A\({}_{5}\) & \(45\) & \(18\),\(250\) & \(219\),\(000\) & \(419\),\(750\) & \(620\),\(500\) & \(821\),\(250\) \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Payment matrix. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & \multicolumn{2}{c}{**Production (P)**} & \multicolumn{2}{c}{**Warehouse Organizers (A)**} \\ \hline  & \multicolumn{2}{c}{**Average Required**} & \multicolumn{2}{c}{**The Probability of**} & \multicolumn{2}{c}{**Strategy Designation,**} & \multicolumn{2}{c}{**There Are Serviceable**} \\
**Strategies Notation, \(\mathbf{P_{j}}\)** & **Number of Starters for Repair, \(\mathbf{n_{j}}\)** & **This Need, \(\mathbf{q_{j}}\)** & **A\({}_{\text{i}}\)** & **Starters in Stock, \(\mathbf{n_{i}}\)** \\ \hline \(\mathrm{P_{1}}\) & \(5\) (0–9) & \(0.1\) & A \({}_{1}\) & \(5\) \\ \hline \(\mathrm{P_{2}}\) & \(15\) (10–19) & \(0.4\) & A \({}_{2}\) & \(15\) \\ \hline \(\mathrm{P_{3}}\) & \(25\) (20–29) & \(0.3\) & A \({}_{3}\) & \(25\) \\ \hline \(\mathrm{P_{4}}\) & \(35\) (30–39) & \(0.1\) & A \({}_{4}\) & \(35\) \\ \hline \(\mathrm{P_{5}}\) & \(45\) (40–50) & \(0.1\) & A \({}_{5}\) & \(45\) \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Strategies of the sides. \begin{table}
\begin{tabular}{c c c} \hline \hline  & \multicolumn{2}{c}{**Winning in RUB**} \\ \cline{2-4}
**Situations** & **Lesion** & **Profit** \\ \hline Storage in the warehouse of & \(-1825\) & - \\ \hline Satisfying the need for one & - & 18,250 \\ starter & - & 18,250 \\ \hline Starter to fulfill the & \(-26\),\(400\) & - \\ \hline \end{tabular}
\end{table} 
Table 9: Conditions for determining winnings. From the profit matrix, we choose the optimal strategy A\({}_{5}\) (n\({}_{5}\) = 45) that provides the maximum profit (b\({}_{\rm i}\)) max = RUB 359,525. The results obtained for the change in profit depending on the stock of starters in the warehouse (strategies A) are shown graphically (Figure 3). We determine the economic effect of using the optimal strategy. Demand for starters in stock: n\({}_{\rm c}\) = 0.1-5 + 0.4 \(\cdot\) 15 + 0.3 \(\cdot\) 25 + 0.1 \(\cdot\) 35 + 0.1 \(\cdot\) 45 = 22 units. The presence of twenty-two units in the warehouse corresponds as closely as possible to strategy A\({}_{3}\), which provides an average gain of b\({}_{\rm c}\) = RUB 256,600 (Table 11). Thus, the economic effect when using the optimal strategy is E (A\({}_{5}\)\({}^{\circ}\)) = 0.29 or 29%