# Multi-Agent Simulation Approach for Modular Integrated Construction Supply Chain
## 2 Related Works
### Simulation Applications in MiC Logistics  
In the context of MiC, transporting and managing logistics presents significant challenges. These include ensuring the timely and cost-effective delivery of modules, optimizing routes to reduce transportation costs and environmental impact, coordinating large-scale prefabricated modules, and managing their transportation efficiently. Traditional logistics systems often struggle with these demands due to their inflexibility and limited adaptability to the dynamic requirements of modular construction.  
Simulation techniques have emerged as crucial tools for addressing these complex logistics challenges. By leveraging simulation, researchers can model the complex interactions between all actors and stakeholders involved, including the suppliers of components, MiC manufacturers, transporters, and project managers. This modeling is essential for ensuring efficient decision-making and project execution. Three primary simulation paradigms are commonly used:  
* Discrete event simulation (DES): used to model the operation of a system as a discrete sequence of events in time, effective for systems where the state changes at specific points, such as the arrival of trucks or the completion of module assembly tasks [36].
* Agent-based simulation (ABS): models the individual behaviors of agents, representing various entities in the logistics network, such as trucks, warehouses, or modules. Each agent operates based on a set of rules, and their interactions can lead to complex system behavior. This paradigm is highly suitable for capturing the dynamic and stochastic nature of MiC supply chain [23].
* System dynamics (SD): focuses on the feedback loops and time delays affecting the entire system's behavior, useful for strategic-level decision-making and long-term planning [37].  
Numerous studies have addressed the challenges of logistics planning in off-site construction (OSC), including MiC. These studies have primarily addressed a single supply chain stage and have addressed issues like inventory management [38], vehicle routing [39], and integrated truck planning [40]. Some researchers have proposed optimization models that integrate various supply chain stages, such as combining production with logistics [41] and logistics with installation [42]. These integrated approaches aim to provide more holistic solutions but often ignore the uncertainties and dynamic interactions, which are critical in real-world applications. To address these limitations, some researchers have employed DES simulation [43], which allows for the modeling of complex logistics processes over  
Figure 2: Steps and substeps for the modular integrated construction (MiC) process.  
time. Some studies have integrated multi-method simulation models with optimization approaches, providing a more robust framework that accounts for both dynamic interactions and stakeholder decisions [44; 45; 46]. By combining these varied approaches, the literature demonstrates significant advancements in addressing the logistical complexities of MiC supply chains. However, further research is needed to develop models that holistically integrate all stages of the supply chain while accounting for uncertainties and dynamics.  
Table 1 summarizes the focus and limitations of each related study, showing how the proposed study addresses gaps in the current literature by providing a more comprehensive and integrated approach to the MiC supply chain.