An Agent-Based Simulation and Optimization Approach for Sustainable Urban Logistics: A Case Study in Lisbon  
[PERSON]  
1 Department of Economics, Management, Industrial Engineering and Tourism (DEGET), University of Aveiro, Campus Universitario de Santiago, 3810-193 Aveiro, Portugal; [EMAIL_ADDRESS] (R.B.L. ); [EMAIL_ADDRESS] (A.L.R. ); [EMAIL_ADDRESS] (I.V.F. ); [EMAIL_ADDRESS] (D.C.)
2 Department of Economics, Management and Industrial Engineering/CIDMA, University of Aveiro, Campus Universitario de Santiago, 3810-193 Aveiro, Portugal
3 Governance, Competitiveness and Public Policies (COVCOPP) Research Unit, University of Aveiro, Campus Universitario de Santiago, 3810-193 Aveiro, Portugal  
4 Industrial Engineering Department, Federal University of Rio Grande do Sul, [PERSON], 99, 5 th Floor, Porto Alegre 90035-190, Brazil; [EMAIL_ADDRESS]  
[PERSON]  
1 Department of Economics, Management, Industrial Engineering and Tourism (DEGET), University of Aveiro, Campus Universitario de Santiago, 3810-193 Aveiro, Portugal  
2 Department of Economics, Management and Industrial Engineering/CIDMA, University of Aveiro, Campus Universitario de Santiago, 3810-193 Aveiro, Portugal
concerns, intensify logistical challenges while fostering innovative solutions to minimize impacts and maximize the efficiency of urban operations. According to [PERSON] et al. (2018), the field of urban logistics remains fragmented, making it challenging to achieve a holistic understanding and identify critical research gaps. Despite this, systematic studies, such as those by [PERSON] et al. (2018) and [PERSON] (2018), have advanced the field by addressing core challenges, including Location-Routing Problem (LRP), Transshipment Location Problem (TLP), and Pickup and Delivery Problem (PDP). PDP stands out among these problems due to its complexity and its pivotal role in enhancing operational efficiency and sustainability in urban logistics. [PERSON] et al. (2018) mention that PDP focuses on optimizing the movement of goods between specific origins and destinations, considering constraints such as time windows, capacity, and urban traffic dynamics. Its prominence in the literature underscores its importance in addressing the growing demands of modern urban environments, making it a key area for technological and methodological advancements in the field. In the classical PDP formulation, a set of capable vehicles must be selected to fulfill customer requests. The request consists of picking up the merchandise at the original point and delivering it to the destination point. The same vehicle can carry multiple requests at the same time, if the total load does not exceed its capacity. For each request, the visit to the point of origin must occur before the visit to the point of destination. Furthermore, both locations must be visited by the same vehicle, except in cases of transshipment, where the order may be fulfilled by another available car. Each destination of origin and destination must be visited exactly once. Given the significance of the problem and the rise in e-commerce driven by advancements in communication technologies, the PDP and its variants have garnered increasing attention in recent years ([PERSON] et al., 2018; [PERSON] et al., 2018). One of the variants introduces transshipment points, leading to the formulation of the Pickup and Delivery Problem with Transshipment (PDP-T) in the literature ([PERSON] et al., 2018; [PERSON] et al., 2018). Unlike the classic PDP, the PDP-T permits goods to be transported by multiple vehicles. According to [PERSON] and [PERSON] (2018), this approach optimizes time and vehicle capacity utilization, offering potential enhancements in logistics operations. Furthermore, time constraints are a critical factor in real-world scenarios, influencing order receipt and delivery.