Scholarlink

<p>Iron and steel industry is a significant basic industry, where steelmaking–refining–continuous casting (SRCC) is a bottleneck. Efficient SRCC schedules can enhance the iron and steel production productivity greatly. SRCC scheduling problems are important and challenging industrial scheduling problems, as well as well-known nondeterministic polynomial time-hard problems. In the realistic SRCC process, the last production stage’s processing times are controllable, and the corresponding scheduling problems are named SRCC scheduling problems with controllable processing times (CPTs). To deal with the SRCC scheduling problems with CPTs efficiently, a new neighborhood structure (named restricted multiswap) and a new decoding method based on domain knowledge, and then a hybrid evolutionary algorithm (HEA) are proposed. The proposed HEA integrates several distinguished features: the aforementioned neighborhood structure and decoding method, local search, biased probability-guided crossover, and two diversification strategies including perturbation and mutation. The HEA achieves the lowest average relative percentage increase (RPI) in comparison with seven state-of-the-art scheduling algorithms, with the average RPI of 0.02%, 0.05%, 0.09% under time limits of 10, 20, and 30&#xa0;s, respectively.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A hybrid evolutionary algorithm based on new neighborhood structure for steelmaking–refining–continuous casting scheduling problems with controllable processing times

  • 期刊论文

  • 发表日期：

    2026年7月20日

查看全文
  • Kun-Kun Peng,
  • Gong-Zhuang Peng,
  • Chun-Jiang Zhang,
  • Wei-Ming Shen,
  • Quan-Ke Pan,
  • Xu-Dong Deng

摘要

Iron and steel industry is a significant basic industry, where steelmaking–refining–continuous casting (SRCC) is a bottleneck. Efficient SRCC schedules can enhance the iron and steel production productivity greatly. SRCC scheduling problems are important and challenging industrial scheduling problems, as well as well-known nondeterministic polynomial time-hard problems. In the realistic SRCC process, the last production stage’s processing times are controllable, and the corresponding scheduling problems are named SRCC scheduling problems with controllable processing times (CPTs). To deal with the SRCC scheduling problems with CPTs efficiently, a new neighborhood structure (named restricted multiswap) and a new decoding method based on domain knowledge, and then a hybrid evolutionary algorithm (HEA) are proposed. The proposed HEA integrates several distinguished features: the aforementioned neighborhood structure and decoding method, local search, biased probability-guided crossover, and two diversification strategies including perturbation and mutation. The HEA achieves the lowest average relative percentage increase (RPI) in comparison with seven state-of-the-art scheduling algorithms, with the average RPI of 0.02%, 0.05%, 0.09% under time limits of 10, 20, and 30 s, respectively.