随机库存路径问题的P-鲁棒性方法

IF 0.4 Q4 ENGINEERING, MULTIDISCIPLINARY Ingenieria Pub Date : 2022-01-05 DOI:10.14483/23448393.18468
Carlos Franco Franco, Juan Carlos Figueroa–García, Juan Sebastían Tenjo-García
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引用次数: 0

摘要

背景:通过数学优化来解决物流问题的方法在文献中被广泛研究,因为它们对商业运作和计算复杂性的重要性。因此,研究与操作相关的不确定性是建模和决策的关键因素。方法:建立了考虑需求变化情况下库存路径问题的随机数学模型。为了得到一个合适的方法,提出了p-鲁棒性方法和经典IRP的重新表述。结果:所进行的实验表明,当在IRP实例中分析不确定性时,通过p稳健方法包括不确定性的好处。此外,给定所选的建模,可以分析组合这些方法的好处。结论:随机决策方法的发展应用于IRP,使分析师能够处理不确定性,并在同一模型中结合不同类型的问题(路线+库存)时降低决策的复杂性。
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A P-Robustness Approach for the Stochastic Inventory Routing Problem
Context: Approaches to logistics solutions through mathematical optimization are widely studied in the literature given their importance for business operations and their computational complexity. In this way, studying the uncertainty associated to operations is a key factor in modeling and decision-making. Method: A stochastic mathematical model is proposed for the Inventory Routing Problem (IRP), considering scenarios with variation in the demands. To obtain a suitable approach, a p-robustness approach and the reformulation of the classical IRP are presented. Results: The performed experiments show the benefits of including uncertainty through a p-robust approach when they are analyzed within an instance of the IRP. Moreover, given the selected modeling, the benefits of combining the approaches can be analyzed. Conclusions: The development of stochastic approaches for decision-making applied to the IRP allow analysts to handle uncertainty and also reduce the complexity of decision when combining different types of problems (Routing + Inventory) in the same model.
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来源期刊
Ingenieria
Ingenieria ENGINEERING, MULTIDISCIPLINARY-
CiteScore
0.70
自引率
25.00%
发文量
33
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