Multi-objective optimization of scrap steel electric furnace SCC scheduling considering CO2 emission and minimization of maximal heat waiting time

Ye Yang, Weida Chen, Li Wei
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引用次数: 1

Abstract

Under the carbon emission reduction policy, iron and steel enterprises are faced with huge pressure of carbon emission reduction. In the process of melting scrap steels using electric furnaces, the heats (jobs) are always assigned with different processing routes, and types of the parallel electric furnaces at each production stage are usually different. First, combining these characteristics, a model considering carbon emission and minimization of maximal heat waiting time for multi-objective optimization of scrap steel electric furnace steelmaking and continuous casting (SCC) scheduling is built. Three objectives, i.e. carbon emission, maximal heat waiting time and makespan, are involved in the model. Then the non-dominated sorting genetic algorithm-II (NSGA-II) suitable for solving the problem is designed accordingly. Finally, the numerical analysis shows that the algorithm can obtain satisfactory solution, considering the objective of minimizing maximal heat waiting time is beneficial to avoid the risk of rescheduling, and the research can help decision makers achieve the target of carbon emission reduction ensuring continuous and efficient SCC production.
考虑CO2排放和最大热等待时间最小化的废钢电炉SCC调度多目标优化
在碳减排政策下,钢铁企业面临着巨大的碳减排压力。在使用电炉熔化废钢的过程中,加热(作业)总是被分配不同的加工路线,并且在每个生产阶段并联电炉的类型通常不同。首先,结合上述特点,建立了考虑碳排放和最大热等待时间最小化的废钢电炉炼钢连铸调度多目标优化模型。模型涉及碳排放、最大热等待时间和最大完工时间三个目标。在此基础上,设计了适合求解该问题的非支配排序遗传算法-ⅱ(nsga -ⅱ)。最后,数值分析表明,该算法能够得到满意的解,考虑到最小化最大热等待时间的目标有利于避免重调度的风险,该研究可以帮助决策者实现碳减排的目标,保证连续高效的SCC生产。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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