对销售价格和绿色水平依赖需求的生产模型的北极松鼠优化算法的应用,具有间隔不确定性
Hachen Ali1, Md Al-Amin Khan2,3, Ali Akbar Shaikh4
1Department of Mathematics, The University of Burdwan, Burdwan, 713104, India.
Scientific reports
|July 28, 2025
概括
这项研究引入了一种新的易腐烂库存模型,将环境因素纳入需求和成本. 北极的优化算法有效地解决了这一可持续库存管理问题.
科学领域:
- 运营研究 运营研究
- 可持续的供应链管理
- 环境经济学环境经济学
背景情况:
- 由于不环保的制造业造成的环境污染日益增加,需要可持续的做法.
- 消费者对环境问题的认识推动了对环保产品的需求,增强了生态可持续性.
- 当前的库存模型往往缺乏整合环境属性和特定的易腐产品挑战.
研究的目的:
- 提出一种新的易腐物库存模型,将环境属性纳入需求和成本函数.
- 解决易腐烂库存管理方面的挑战,包括产品寿命,季节性需求和预付款.
- 开发一个能够考虑绿色产品水平,价格敏感需求,区间估值持有成本和部分积压的模型.
主要方法:
- 开发一种易腐商品库存模型,客户需求取决于绿色水平和价格.
- 包括区间估值的持有成本和线性时间依赖的持有成本.
- 利用Arctic Puffin优化 (APO) 算法来解决区间值目标函数最大化问题,并与其他七种优化算法进行比较.
主要成果:
- 拟议的模型成功地将环境属性纳入易腐的库存管理中.
- 与其他测试过的算法相比,Arctic Puffin Optimization (APO) 算法在解决优化问题的过程中表现出了卓越的性能.
- 后优化分析提供了对各种库存参数对模型结果的影响的见解.
结论:
- 该研究为可持续的易腐货物库存建模提供了一个理论框架.
- 开发的模型为企业提供了实际影响,旨在实现对环境负责任的库存管理.
- 将环境考虑纳入库存模型对于提高生态可持续性和减轻污染至关重要.
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