## 4 Case Study of Lisbon  
A simulation was conducted in the city of Lisbon, Portugal. Lisbon is the largest city in the country and its capital, strategically positioned on the right bank of the Tagus River along the Atlantic coast, making it the westernmost capital of mainland Europe. Covering an area of approximately 100.05 km\({}^{2}\), Lisbon serves as the core of the Lisbon Metropolitan Area (LMA), which encompasses 18 municipalities over an area of about 3015.24 km\({}^{2}\). This metropolitan region is the most populous in Portugal, housing nearly 3 million inhabitants, representing approximately 25% of the national population, with an average population density of 956.4 inhabitants per km\({}^{2}\). Recognized as a key political, economic, and cultural hub, Lisbon plays a vital role in the integration and development of the municipalities within the LMA, including cities such as Sintra, Cascais, Almada, and Setubal. Figure 4 illustrates the area where the simulation was applied, with a maximum permitted speed of 50 km/h incorporated into the model. Additionally, an average speed of 30 km/h was used throughout the simulation to reflect realistic driving conditions. The company operates with at least three drivers/vehicles, designated as A, B, and C, to carry out pickup and delivery tasks. The allocation of these vehicles follows the company's predefined priority order, ensuring an optimized dispatch strategy aligned with operational preferences. The maps in Figure 4 illustrate the spatial distribution of tasks on the day with the highest number of orders. Figure 4a shows the scenario at the pickup stage, while Figure 4b represents the delivery stage. The yellow envelope symbol corresponds to the assigned tasks, the yellow warehouse icon indicates the fixed storage unit, and the truck icons represent the drivers performing the tasks. Both views are focused on the Lisbon metropolitan area, the company's main operating area. The company under study operates in the cities of Lisbon and Porto, Portugal, providing flexible and on-demand baggage pickup and delivery services. However, this article focuses exclusively on the operations carried out in Lisbon. Customers can request services through various platforms, including the company's mobile application, official website, or airline ticket booking platforms. To ensure operational efficiency, orders must be placed at least two hours in advance, allowing operators to assign tasks to available drivers. The allocation follows a predefined priority order, with Driver A being the first choice; if unavailable, the task is reassigned to Driver B, and, if necessary, to Driver C. Additionally,  
Figure 4: Simulation area and route analysis for pickup and delivery operations. orders placed one day in advance are consolidated and distributed to drivers at 7:00 AM each day, with the possibility of adjustments throughout the day, provided that the two-hour minimum lead time and priority selection criteria are respected. The operational model also considers a maximum capacity of 24 baggage volumes per vehicle, as detailed in Section 3.1. Table 3 presents a summary of the orders processed by the company within this operational framework. To ensure the accuracy and reliability of the ABS model, a rigorous validation process was conducted. Initially, the logical consistency of the model was verified, ensuring that the  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Driver** & **Pickup Date** & **Pickup Time** & **Delivery Date** & **Delivery Time** & **Baggage Volume** & **Pickup** & **Delivery** \\
**Pickup-Delivery** & **Pickup Date** & **Pickup Time** & **Delivery Date** & **Delivery Time** & **Baggage Volume** & **Logitude,** & **Logitude,** \\  & & & & & & & & \\  & & & & & & & & \\ \hline B-A & 31 December 2022 & 12:00 &  
Order/Task, Vehicle, and Warehouse agents accurately represented operational processes and interactions within the company studied. The behavior of each agent was analyzed to confirm its adherence to real-world system expectations.