在纸箱制造系统中,用于不确定的供应商 - 材料选择问题,采用扩展目标编程方法,并具有逐步惩罚函数
Zahra Najibzadeh1, Hamid Reza Maleki2, Sadegh Niroomand3
1Department of Mathematics, Shiraz University of Technology, Shiraz, Iran.
Scientific reports
|September 5, 2024
概括
这项研究优化了纸板箱的材料和供应商选择,最大限度地减少浪费,成本和过度生产. 一种新的方法处理专家驱动的不确定性,以实现更现实的生产规划.
科学领域:
- 运营研究 运营研究
- 工业工程 工业工程 工业工程
- 供应链管理 供应链管理
背景情况:
- 多目标优化对于复杂的工业问题至关重要.
- 现实世界的生产面临着不确定性,经常受到专家意见的影响.
- 现有的模型可能无法充分解决材料和供应商选择中的信念程度不确定性.
研究的目的:
- 解决纸箱生产中的多目标材料和供应商选择问题.
- 在以信念为基础的不确定环境中使用正常分布来制定问题.
- 开发一种新的解决方案方法,以优化浪费,成本和过度生产.
主要方法:
- 在一个信仰程度不确定的环境中制定问题.
- 将不确定的配方转换为清晰的形式,使用机会受约束的编程.
- 开发一个目标编程方法,并对多目标的问题进行逐步惩罚函数.
主要成果:
- 一个案例研究证明了拟议的配方和解决方案方法的有效性.
- 这种方法成功地优化了总浪费,系统成本和纸板箱过剩.
- 与现有方法进行比较,突出了拟议方法的效率.
结论:
- 提出的方法有效地处理材料和供应商选择中的不确定性.
- 它为优化纸箱生产中的多个目标提供了一个强大的框架.
- 这种方法为提高行业效率和减少浪费提供了有价值的工具.
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