![]() ![]() Also, the optimized solutions reduce the project duration, total costs, and emissions by 28%, 50%, and 17%, respectively. The DOE analysis indicates that some logistics decisions significantly influence construction KPMs (e.g., project duration, construction costs, construction emissions) and vice versa, calling for more collaboration between stakeholders. The developed approach is applied to a real case study. Third, metamodeling finds the near-optimum logistics and construction decisions (e.g., trucks' number, their dispatching time, ship capacity, inventory, resource planning) that enhance KPMs. Second, design of experiments (DOE) reveals the main and interaction effects between logistics and construction decisions that significantly affect KPMs, such as the project duration, total costs, and carbon emissions. First, hybrid multi-agent simulation models the communications between ML-MiC stakeholders and their internal operations. These objectives are achieved by developing a holistic modelling approach that integrates three methods. This paper fills this gap by achieving the following objectives: 1) simulate the internal operations of ML-MiC stakeholders (e.g., manufacturers, logistics service providers, contractors) and their interactions 2) identify the significant decisions that impact the key performance measures (KPMs) of ML-MiC and 3) obtain the near-optimum decisions that improve the sustainability of ML-MiC. However, the literature lacks decision support systems (DSS) to simulate, analyze, and optimize ML in MiC (ML-MiC). Multimodal logistics (ML), which involves multiple transportation modes, has been increasingly used in many Modular integrated Construction (MiC) projects. ![]()
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