# Pallet Picking Strategy in Food Collecting Center
## 6 Simulation Model and Results  
A simulation model was implemented in order to identify the optimal warehouse layout for different agro-food collecting centers, adopting the proposed model. In the case hereby presented, the stocking of the three-different classes of items identified as \(A\), \(B\), and \(C\) is considered, with each of them being characterized by a specific turnover index ratio (\(I_{A}\), \(I_{B}\), and \(I_{C}\)), whose values are listed below:  
* \(I_{A}\) = 90 the items are picked very frequently in a given interval time;
* \(I_{B}\) = 12 the items are picked occasionally in a given interval time;
* \(I_{C}\) = 3 the items are picked rarely in a given interval time.  
The parameter \(I\) is assumed to embrace a season, therefore the goods from the collecting center are considered to be seasonal food. Four different scenarios are evaluated considering the same value of \(N\) parameters for each case; in Table 1 it is possible to observe that the percentage of the different classes of items to be stocked in the collecting center change significantly for each scenario.  
The model allows the evaluation of the environmental (measured as Carbon Footprint) and economic impacts (measured as Management Costs) due to material handling activities adopting a collecting center with different layouts and with forklifts powered by internal combustion or electric engine. The strategy suggested by the model is shown in the following tables, in four different scenarios, in order to minimize the Carbon Footprint (Table 2) and Management Costs (Table 3).  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multicolumn{4}{c}{**Percentage of A, B, and C-Items Stocked in Warehouse**} \\ \hline
**Scenarios** & **A (\%)** & **B H (\%)** & **C (\%)** \\ \hline
#1 & 100 & 0 & 0 \\
#2 & 70 & 20 & 10 \\
#3 & 40 & 30 & 30 \\
#4 & 20 & 50 & 30 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Hypothesis of the stored goods in the warehouse over the time, according four different scenarios corresponding to different mix of ABC classes.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multicolumn{4}{c}{**Input Parameters**} & \multicolumn{3}{c}{**Output (minimal CP)**} \\ \hline
**Scenarios** & **N (u)** & **A (\%)** & **B (\%)** & **C (\%)** & **Layout** & **MHE** \\ \hline
#1 & 120 & 100 & 0 & 0 & Fishbone & Electric-forklifts \\
#2 & 120 & 70 & 20 & 10 & Fishbone & Electric-forklifts \\
#3 & 120 & 40 & 30 & 30 & Longitudinal/Transversal & Electric-forklifts \\
#4 & 120 & 20 & 50 & 30 & Longitudinal/Transversal & Electric-forklifts \\ \hline \hline \end{tabular}
\end{table}
Table 2: Layout and Material Handling Equipment (MHE) identified in order to minimizing of the Carbon Footprint due to inbound material handling.  
It is possible to observe that the layouts suggested by the model in the collecting center, change on the basis of the mix of the goods to be stocked. In particular, the environmental impact is reduced by approximately of 10% adopting the fishbone layout in cases identified as #1 and #2. Instead, in cases #3 and #4 the longitudinal and the transversal layouts ensured a reduction of Carbon Footprint by approximately of 1% (see Figure 6a). Although the fishbone layout ensured a lower average path for the handling of the goods, it requires a collecting center with larger surface area compared to the one calculated for the longitudinal and transversal layouts. As a result, the Management Costs of fishbone layouts averages 20% higher than the longitudinal and transversal layout in terms of economic scores (see Figure 6b).  
Regarding the MHE evaluation, the electric forklift adoption gives the best results in terms of environmental and economical performances both. Indeed, in the cases analyzed, the electric forklift ensured a reduction of about 50% of Carbon Footprint and a _OCs_ saving of about 20% when compared to LPG-forklift.