概括
本研究引入了一个强大的热生产计划模型,同时解决了板材选择,碳税法规和加工时间的不确定性. 新方法提供高质量,强大的解决方案,有效地,与决定性方法相比,成本增加最小.
科学领域:
- 运营研究 运营研究
- 制造业 工程 制造工程
- 环境管理环境管理
背景情况:
- 热生产时间表 (HRPS) 在钢铁制造中至关重要.
- 关键的挑战包括板块选择,碳税合规性和处理时间的不确定性.
- 现有的方法很难有效地整合这些因素.
研究的目的:
- 开发一种新的,强大的HRPS模型 (RHRPSP-CTR),结合板块选择,碳税和不确定的处理时间.
- 为了应对最糟糕的碳排放和不确定性下完成时间的复杂性.
- 为大规模的RHRPSP-CTR实例提出一个高效的算法.
主要方法:
- 开发了一个强大的对应模型,使用预算不确定性集和二元化.
- 采用动态编程用于最坏情况下的碳排放和完成时间评估.
- 设计了一个具有板块选择和重量更新策略的自适应性大邻里搜索算法.
主要成果:
- 拟议的方法可以为小型实例快速实现最佳解决方案,并为大型实例快速实现高质量,稳健的解决方案.
- 强大的HRPS方案与确定性方法相比,只会导致边际成本增加.
- 更高的碳税并不能保证更低的碳排放;不确定性参数并不总是增加排放.
结论:
- RHRPSP-CTR模型有效地平衡了生产效率,碳税法规和处理时间的不确定性.
- 适应性大邻里搜索算法为复杂的大规模调度问题提供了有效的解决方案.
- 这些发现为优化环境和运营约束下的钢铁制造提供了宝贵的见解.
相关概念视频
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