Optimization of Precast Concrete Production with a Differential Evolutionary Algorithm

Abstract

This study investigates the limitations of existing models in optimizing equipment resource allocation for the large-scale production of precast concrete components in highway engineering. There are abundant investigations on scheduling models of precast concrete components. However, there is a scientific problem that previous models often overlooked the interruptibility of specific processes and the possibility of performing tasks outside of regular working hours, leading to suboptimal resource utilization. To address this limitation, an improved differential evolution (DE) algorithm was developed, which incorporates an adaptive mutation operator and a dual mutation strategy to enhance population diversity and accelerate convergence speed. The proposed optimization model significantly reduced equipment resource consumption. In a real-world case study, the model achieved an 11.11% reduction in project duration and a 21.4% increase in production capacity under the same resource configuration. The improved DE algorithm demonstrated superior performance in maintaining population diversity and accelerating convergence. These findings provide a scientifically grounded approach for enhancing productivity and resource efficiency in prefabricated construction, with potential applications extending beyond highway projects.