关键词: 预制构件定点制造, 二维布局, 最佳适应算法, 自适应遗传算法, 协同优化

Abstract: To minimize tardiness penalty costs in the fixed-location manufacturing of precast concrete components,a bilevel Mixed-Integer Linear Programming (MILP) model and a Perturbation-Restart Hierarchical Best-Fit Adaptive Genetic Algorithm (PRHBF_AGA) were proposed.The bilevel MILP model addressed small-scale problems:the first-level model optimized workpiece grouping and two-dimensional mold table layouts,while the second-level model refined the layout and scheduling based on the outputs of the first.For medium-and large-scale problems,PRHBF_AGA divided the problem into two parts-layout and scheduling.The best-fit algorithm optimized the layout,and the adaptive genetic algorithm managed scheduling.A variable neighborhood search and a perturbation-restart mechanism were incorporated to prevent premature convergence and improve solution quality and efficiency.Additionally,six intelligent optimization algorithms based on alternating iterative frameworks were designed for comparative analysis.Computational experiments demonstrated the effectiveness and competitiveness of the proposed MILP model and PRHBF_AGA,highlighting their applicability in optimizing layout and scheduling in precast component production.

Key words: fixed-point manufacturing of prefabricated components, two-dimensional layout, best-fit algorithm, adaptative genetic algorithm, collaborative optimization