This article studies a steelmaking-continuous casting (SCC) scheduling problem by considering ladle allocation. It takes technological rules in steel manufacturing and ladle-related constraints into account. A scheduling problem is formulated to determine allocation equipment for jobs, production sequence for jobs processed by the same equipment, and modification operations for empty ladles after their service for jobs. To ensure the fastest production and least energy consumption, we present a mixed integer mathematical programming model with the objectives to minimize the maximum completion time, idle time penalties, and energy consumption penalties related to waiting time. To solve it, we develop a two-stage approach based on a combination of scatter search (SS) and mixed integer programming (MIP). The first stage applies an SS algorithm to determine the assignment and sequence variables for charges. For the obtained solution, we construct a temporal constraint network and establish an MIP model at the second stage. We apply ILOG.CPLEX to solve the model and find the final solution. We analyze and compare the performance of the proposed approach with a hybrid method that combines a genetic algorithm with MIP on instances constructed from a real iron-steel plant. To further verify the effectiveness of the proposed algorithm, we compare its results with optimal solutions of the constraint-relaxed original problem. The experimental results show the effectiveness of the proposed approach in solving the SCC-scheduling problem.

中文翻译：

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优化节能炼钢连铸的混合分散搜索算法


本文研究了考虑钢包分配的炼钢连铸（SCC）调度问题。它考虑了钢铁制造中的技术规则和钢包相关的限制。制定调度问题以确定作业的分配设备、同一设备处理的作业的生产顺序以及空钢包在作业服务后的修改操作。为了确保最快的生产和最少的能源消耗，我们提出了混合整数数学规划模型，其目标是最小化最大完成时间、空闲时间惩罚以及与等待时间相关的能源消耗惩罚。为了解决这个问题，我们开发了一种基于分散搜索（SS）和混合整数规划（MIP）组合的两阶段方法。第一阶段应用SS算法来确定费用的分配和序列变量。对于得到的解，我们在第二阶段构建了时间约束网络并建立了 MIP 模型。我们应用ILOG.CPLEX来求解模型并找到最终的解决方案。我们对所提出的方法与混合方法的性能进行了分析和比较，该混合方法将遗传算法与 MIP 结合在由真实钢铁厂构建的实例上。为了进一步验证所提出算法的有效性，我们将其结果与约束松弛的原始问题的最优解进行了比较。实验结果表明了该方法在解决SCC调度问题上的有效性。