The inventory location problem under periodic inventory control policy (R, S): modeling, solving and analysis

The Periodic Inventory control policy ( R , S ) is one of the most employed and studied strategies by practitioners and researchers in a variety of contexts. In the last two decades, Inventory Location literature has been focused on the integration of inventory control issues into facility location...

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Vydáno v:Optimization and engineering Ročník 26; číslo 3; s. 1957 - 2029
Hlavní autoři: Olivares-Alvarez, Luis, Miranda-Gonzalez, Pablo A., Tapia-Ubeda, Francisco J., Cannella, Salvatore
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.09.2025
Springer Nature B.V
Témata:
Benders decomposition
Commodities
Control
Customers
Decision making
Decomposition
Engineering
Environmental Management
Financial Engineering
Integer programming
Inventory control
Mathematics
Mathematics and Statistics
Mixed integer
Network design
Operations Research/Decision Theory
Optimization
Performance evaluation
Research Article
Supply chain management
Supply chains
Systems Theory
Variables
Warehouses
Periodic review
Inventory location problems
Generalized benders decomposition
Supply chain network design
Inventory control
)
,
Risk-pooling
ISSN:1389-4420, 1573-2924
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Shrnutí:The Periodic Inventory control policy ( R , S ) is one of the most employed and studied strategies by practitioners and researchers in a variety of contexts. In the last two decades, Inventory Location literature has been focused on the integration of inventory control issues into facility location models for addressing Supply Chain Network Design problems. However, most of Inventory Location related research mainly focus on other inventory control policies, such as the continuous review policy ( s , Q ), denoting a significant unfilled research gap. Thus, this research proposes and formulates an Inventory Location Problem under a Periodic Inventory control policy ( R , S ) as a novel Mixed Integer, Nonlinear, Nonconvex Programming model to deal with Supply Chain Network Design. In addition, and according to the high problem complexity, an efficient and effective solution approach based on the Generalized Benders decomposition is proposed and implemented to solve the proposed formulation. In a wide variety of synthetic sized tested instances, the algorithm reached global optimality (i.e., zero duality gap), mostly in competitive times" has been replaced with "80% of the instances (768 out of 960) were solved in less than 30 s. The proposed formulation, along with the solution approach, provides a useful decision support methodology for designing the Supply Chain Network where the inventory control policy ( R , S ) is employed. Based on this research, significant research and managerial insights are presented and discussed.
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ISSN:1389-4420
1573-2924
DOI:10.1007/s11081-025-09963-2