A multi-product, multi-period model to select supplier for deteriorating products while considering uncertainty as well as backorder

Artikel

Determining supplier and optimum order of the quantity is an issue of great importance in logistics management for many companies. In this regard, it is crucial to determine the best decisions for the order quantity as well as the most suitable supplier through considering existing limitations and uncertainties. To optimize a multi-product, multi-period model with select supplier for deteriorating products, while uncertainty of future economic conditions directly affects the problem conditions. In this regard, a mixed integer definite programing model is introduced, and afterwards, the proper robust structure is established through a two-phase scenario-based approach. The behavior of the main features of the inventory system elaborated upon in this article, that is, multi-product, uni-level, multi-period inventory system, has been modeled under the influence of uncertain economic environment. In the final phase pattern, search method is employed to determine proper answers, the results of which are analyzed, to shed light on various aspects of the solving procedure, as well as the problem itself. The applicability of the proposed model is shown by an illustrative example.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: Journal of Industrial Engineering International ; ISSN: 2251-712X ; Volume: 15 ; Year: 2019 ; Issue: 1 ; Pages: 93-101 ; Heidelberg: Springer

Classification and Topics

• Classification: Management
• Subject: Deteriorating items ; Inventory control ; Robust optimization ; Pattern search ; Scenario based

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Lashgari, Mohsen ; Sadjadi, Seyed Jafar ; Sahihi, Misugh
• Event: Veröffentlichung
• (who): Springer
• (where): Heidelberg
• (when): 2019

Further information

• DOI: doi:10.1007/s40092-018-0266-6
• Handle: http://hdl.handle.net/10419/267601
• Last update: 10.03.2025, 11:44 AM CET