The construction sector is under increasing pressure to reduce carbon emissions, particularly in logistics and material transportation. This study introduces the BASE model, an integrated methodology designed to enhance sustainability in construction hauling operations.
The BASE model synthesises four key components: Eco-Hauling principles to minimise fuel use and emissions, the Big Room approach to foster stakeholder collaboration, Discrete Event Simulation (DES) via AnyLogic for process modelling, and Response Surface Methodology (RSM) within Stat-Ease for scenario optimisation. Applied to a real-world case study involving the transportation of 900 tonnes of soil, the model is evaluated across three configurations: conventional practice, Eco-Hauling alone, and the integrated BASE strategy.
A comparative analysis conducted under consistent input conditions reveals that the integrated BASE strategy yields a 12.4% reduction in CO2 emissions and diesel consumption, alongside a 42% decrease in vehicle idle time and an approximate 10% cost saving. Further optimisation using Stat-Ease identifies a refined scenario that achieves a 35% reduction in CO2 emissions, a 34.9% decrease in diesel usage, and a 37.8% reduction in overall operational costs.
This study supports the achievement of UN SDGs 9, 11, and 13, illustrating that the BASE model offers a scalable, data-driven framework for advancing sustainable, efficient, and cost-effective construction logistics.
The paper demonstrates the practical viability of integrating collaborative planning and simulation-based optimisation in real construction settings. Future research should explore the integration of IoT and AI for real-time optimisation and predictive logistics management.
