Optimization of the Stacking Plans for Precast Concrete Slab Based on Assembly Sequence

Abstract

Precast concrete (PC) slabs are widely used in the assembly of concrete residential buildings. The PC slabs are manufactured at the factory and then arranged in stacks for transport to the construction site for assembly. Currently, optimization of the stacking plans for PC slabs focuses on yard-space utilization and transportation efficiency and rarely considers the assembly sequence; secondary sequencing of prefabricated elements is required during construction to meet the lifting scheme, which leads to increased construction preparation time and risk of worker injury. To enable stacking crews to generate stacking plans rapidly and systematically to improve the on-site lifting efficiency of the components, this paper proposes a storage-location allocation model with two objectives: reduce secondary-sorting workload and increase stacking stability for PC slabs. At the same time, it must match the characteristics of the problem. To prevent the solution from falling into the local optimum during the evolution of the particle swarm optimization algorithm, we introduce an elitist learning strategy, which can improve the solutions when the group converges. Finally, we verify our allocation model and optimization algorithm through example simulations. The simulation results show that, compared with the traditional method, the stacking plans generated by this method have a lower secondary-sorting workload and higher stacking stability when using the same number of storage racks.