Multi-objective Carbon-efficient Scheduling Optimization of Flexible Off-site Construction Supply Chain
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Abstract
Efficient implementation of off-site construction projects hinges on a well-functioning supply chain. Any deviation from the optimal resource allocation in various stages can lead to problems like idle production machinery, resulting in energy wastage, or prolonged waiting times for transportation vehicles. These issues run counter to the original aim of energy-efficient and high-efficiency off-site construction. In today's digital era, it's imperative to leverage digital twins and optimization technology to seamlessly integrate resource allocation throughout the entire supply chain process. This drives digitalized, efficient collaboration, and sustainable development. This study takes a comprehensive view of the entire process of the off-site construction supply chain, with a primary focus on optimizing resource allocation at each stage. The objective is to establish a responsive and flexible construction supply chain through algorithmic design, while adhering to constraints related to time, cost, and carbon emissions. To start, this research constructs a digital twin to represent the resource allocation for the entire off-site construction supply chain process. Through this, critical factors influencing the comprehensive cost of the supply chain are analyzed, and these factors are established as variables for optimization objectives. Subsequently, we propose a multi-objective, low-carbon collaborative scheduling model tailored for flexible off-site construction supply chains. A program for solving the optimization model is designed based on the NSGA-II algorithm. Lastly, the effectiveness and optimization results of the model algorithm are validated through simulation cases. The results demonstrate that factoring in internal resource allocation within the supply chain in the model can further reduce total time and carbon emission costs. This research, through optimization algorithms, identifies optimal resource allocations for various processes within the supply chain. It determines the scheduling sequence for prefabricated components under variable resource allocation, breaking away from the limitations of scheduling models that often assume a single-machine scenario. The determination of resource allocation will assist in the decision-making process for suppliers and transporters of different scales. Additionally, this study also emphasizes the potential for carbon reduction within the off-site construction supply chain.
