增强三角模糊参数框架,用于固体多目标运输问题,分别使用决策变量
Vishwas Deep Joshi1, Medha Sharma2, Lenka Čepová3
1Department of Mathematics, Faculty of Science, JECRC University, Jaipur, Rajasthan, India. vdjoshi.or@gmail.com.
Scientific reports
|July 29, 2025
概括
这项研究为不确定的运输问题提出了一种新的模糊优化方法. 它通过将模糊数据转化为精确的模型来增强决策,改善物流规划.
科学领域:
- 运营研究 运营研究
- 模糊优化的优化.
- 物流管理物流管理的管理.
背景情况:
- 运输问题往往涉及不确定的参数,如供应,需求和成本.
- 现有的方法在动态环境中难以实现灵活性和弹性.
- 决策需要强大的策略来管理固有的不确定性.
研究的目的:
- 为模糊多目标传输问题 (FMOTPs) 引入一种新的两步通用参数方法.
- 提高在不确定性下物流和运输系统的决策能力.
- 在运输规划中为模糊优化提供一个计算高效的框架.
主要方法:
- 使用三角模糊数 (TFN) 和参数精度参数μ ∈ [0,1].
- 将不精确的模糊数据转化为一系列清晰的多目标传输问题 (CMOTP).
- 采用模糊线性编程 (FLP) 来解决CMOTP,选择基于模糊理想的欧几里德距离的解决方案.
主要成果:
- 与现有模型 (Nomani的方法,模糊的DEA,GRA) 相比,提出的方法显示出更高的性能.
- 实现增强的最佳性接近,解决方案稳定性和排名准确性.
- 数字案例研究验证了该方法的有效性和效率.
结论:
- 新型参数方法为解决FMOTP提供了一个系统和有效的框架.
- 提高管理人员处理不确定性的能力,并优化运输中的权衡.
- 该模型具有可扩展性,适合集成到各种行业的企业物流系统中.
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