A generic decision support framework for inventory procurement planning in distribution centres. (March 2023)

• Record Type: Journal Article
• Authors: Zietsman, H. Jurie; van Vuuren, Jan H.
• Is Part Of: Computers & industrial engineering. Volume 177(2023)
• Publication Date: 2023-03
• Subjects: Inventory procurement -- Time series forecasting -- Decision support systems -- Supply chain management; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2023.109057
• Languages: English
• ISSNs: 0360-8352

Abstract

Abstract: The success of any business depends on how well it is able to satisfy customer demand, while remaining financially viable. Globalisation and the growth of e-commerce have resulted in distribution centres having to manage increasing numbers of products. As the number of products sold increases, so does the complexity of the corresponding inventory planning and management problem. High-quality decision making, in this regard, necessitates the utilisation of computerised decision support systems capable of accommodating the complexity presented by a large number of products. Existing frameworks for decision support in inventory management are mainly focused on a single facet of the inventory management problem — generic, integrated frameworks seem to be absent from the literature. In this paper, a holistic framework design is proposed which integrates all of the major components expected to form part of a generic framework for inventory planning and management. The objective of the framework is to provide decision support in respect of various inventory management operations, such as product selection, product segmentation, demand forecasting and determining the sizes and timings of procurement orders, in pursuit of a desirable balance between the conflicting objectives typically considered in inventory management. Highlights: A framework is proposed for decision support in inventory procurement. The framework is generic and may be adopted in the distribution centres of most businesses. Results obtained during a verification analysis are competitive with benchmarks. The framework is demonstrated within the context of a real-world case study. The case study results show improvements over current operations of the underlying business.