【摘要】 当前，个性定制化与智能信息化是钢铁工业的发展趋势，高效的智能算法可以提高钢铁生产调度的灵活性。本文提出了一种超启发式遗传算法(Hyper-Heuristic-Genetic Algorithm, HH-GA)用于求解加工设备空闲时间最小为优化目标的炼钢-连铸生产调度模型。针对模型构建低层启发式算子，利用自适应遗传算法选择策略对低层启发式算子进行排列组合优化，同时加入模拟退火接受准则，避免算法陷入局部最优。以某炼钢厂主要生产模式下的实际生产计划为仿真算例进行实验，通过案例分析和算法对比，验证了超启发式遗传算法的性能。结果表明，在大规模的案例情况下，超启发式遗传算法的综合性能比遗传算法更优。更多还原

【Abstract】 At present, personalized customization and intelligent informatization are the development trend of steel industry, and the efficient intelligent algorithm can improve the flexibility of steel production scheduling.In this paper, a hyper-heuristic genetic algorithm is proposed to solve the steelmaking continuous casting production scheduling model with the objective of minimizing the idle time of processing equipment.According to the model, the low-level heuristic operators are constructed, and the selection strategy of adaptive genetic algorithm is used to optimize the arrangement and combination of low-level heuristic operators.At the same time, the simulated annealing acceptance criterion is added to avoid the algorithm falling into local optimization.Taking the actual production plan under the main production mode of a steel plant as a simulation example, the performance of hyper-heuristic genetic algorithm is verified through case analysis and algorithm comparison.The results show that in large-scale cases, the comprehensive performance of hyper-heuristic genetic algorithm is better than heuristic algorithm.更多还原