## 4 A Real-Case Scenario Application of the Proposed Algorithm  
In this section, a real-case scenario application of the proposed algorithm is provided. The problem is composed of 54 activations and 51 deactivations (for a total of 105 service operations) which need to be assigned to workers; each operation is described with an account number ID, the location and the time in which the operation has to be completed, an example of the sample is reported in Table 2.  
The algorithm was implemented on a Windows 10 \(\times\) 64, Intel Core i7 CPU 2.40 GHZ, 4 GB RAM. After all the data from the activations and deactivations have been collected (Phase 1), the algorithm provides a solution taking into account all constraints and then allocates operations to the workers, solving the aforementioned Phases 2, 3, 4 as shown in Table 3.  
Figure 5: Improved path. The solution is calculated thanks to the definition of distance and saving matrix for each pair of destinations. Table 3 shows the account number IDs assigned to an operator in time window 1. The two last columns represent the total time of intervention (including transport time) and the not allocated time for each operator, respectively. Table 3 shows that the operator 1 carries out the interventions for IDs 70, 17 and 72 with a total intervention time of 77.2 min, consisting of 60 min of operating time (2 deactivations and 1 activation) and 17 min of travel time. Then, Table 4 reports the workload that has been assigned to each operator throughout the day and information related to the operating time (including travel time) for the whole day. Finally, in order to optimize routes (Phase 5), Table 5 shows the distance from one location to all those located in the same time window. According to Table 5 the position of intervention ID 12 would \begin{table}
\begin{tabular}{c c c c c c c} \hline  & **Total TW1** & **Total TW2** & **Total TW3** & **Total TW4** & **Total TW5** & **Total TW6** & **Total Workload** \\  & **(min)** & **(min)** & **(min)** & **(min)** & **(min)** & **(min)** & **per D****or****or****per Day****(min)** \\ \hline Operator 1 & 76.00 & 56.71 & 0.00 & 53.00 & 33.00 & 55.10 & 274.30 \\ Operator 2 & 74.40 & 47.24 & 0.00 & 58.00 & 49.00 & 32.85 & 261.80 \\ Operator 3 & 73.80 & 48.99 & 20.00 & 47.00 & 32.00 & 49.95 & 272.00 \\ Operator 4 & 68.90 & 47.46 & 47.00 & 58.00 & 0.00 & 65.57 & 286.50 \\ Operator 5 & 66.00 & 32.29 & 49.00 & 54.00 & 44.00 & 0.00 & 245.20 \\ Operator 6 & 65.50 & 37.35 & 0.00 & 57.00 & 49.00 & 55.95 & 264.20 \\ Operator 7 & 65.50 & 58.87 & 0.00 & 65.00 & 52.00 & 34.94 & 275.50 \\ Operator 8 & 49.10 & 47.68 & 51.00 & 34.00 & 31.00 & 47.72 & 260.90 \\ Operator 9 & 56.90 & 0.00 & 0.00 & 64.00 & 50.00 & 38.81 & 209.50 \\ Operator 10 & 0.00 & 0.00 & 0.00 & 50.00 & 50.00 & 35.95 & 135.50 \\ Operator 11 & 0.00 & 0.00 & 0.00 & 30.00 & 51.00 & 36.22 & 117.00 \\ Operator 12 & 0.00 & 0.00 & 0.00 & 30.00 & 30.00 & 32.13 & 92.60 \\ Operator 13 & 0.00 & 0.00 & 0.00 & 15.00 & 42.00 & 57.89 & 114.50 \\ \hline \end{tabular}
\end{table} 
Table 4: Workload assigned to each operator. \begin{table}
\begin{tabular}{c c c c c} \hline
**ID** & **Type of Operation** & **Latitude** & **Longitude** & **ID TW** \\ \hline
0 & Depot & 44.100546 & 8.9401007 & \\
5 & Activation & 44.4039594 & 8.9372752 & TW1 \\
52 & Activation & 44.4052182 & 8.9393867 & TW6 \\
29 & Activation & 44.4025486 & 8.9376078 & TW5 \\
57 & Deactivation & 44.4046075 & 8.9328502 & TW1 \\
78 & Deactivation & 44.4104947 & 8.9323900 & TW6 \\ \hline \end{tabular}
\end{table} 
Table 2: Sample of output dataset expressed in GIS coordinates and relative TW.