经济秩序 量 基于模型的优化 模糊 非线性 动态 数学方案
Kalaiarasi Kalaichelvan1, Nasreen Kausar2, Sajida Kousar3
1PG and Research Department of Mathematics, Cauvery College for Women (Affiliated to Bharathidasan University), Tiruchirappalli 620018, Tamil Nadu, India.
本研究引入了一个模糊的数学方法,通过管理不确定的参数,如短缺和订单成本来优化库存成本. 适应性经济秩序数量模型提高了预测准确性和系统效率,以更好地控制库存.
科学领域:
- 运营研究 运营研究
- 应用数学 应用数学 应用数学
- 库存管理 库存管理
背景情况:
- 库存管理面临的挑战是由于不确定的市场条件影响成本,如短缺,订购和退化.
- 传统模型与波动性参数作斗争,需要先进的方法来准确预测和策略.
- 模糊数学为处理观测数据中的不确定性和不精确性提供了一个强大的框架.
研究的目的:
- 开发一个适应性和整合性的经济秩序量 (EOQ) 模型,利用模糊的数学.
- 管理不确定的库存参数,提高系统精度和计算效率.
- 通过改善公司流程的控制和监控来优化库存成本.
主要方法:
- 使用模糊数字来表示主要支出和不确定的参数.
- 开发一个适应性和整合性的经济秩序数量模型.
- 使用分级平均积分方法来确定溶液.
- 通过视觉图形描绘进行数值和灵敏度分析.
主要成果:
- 拟议的模糊EOQ模型有效地管理库存系统中的不确定参数.
- 该模型显示在库存成本管理中提高了精度和计算效率.
- 数字和灵敏度分析验证了模型的性能和适用性.
- 该研究为优化库存成本和增强系统开发提供了一个结构.
结论:
- 模糊的数学方法对于在不稳定的环境中准确预测至关重要.
- 开发的模糊EOQ模型为库存成本优化提供了可靠的方法.
- 综合模型增强了库存系统的性能,控制和监控能力.
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