A mixed inventory model with variable lead time and random back-order rate

Researchers have given a lot of attention to the integrated vendor-buyer problem. Both deterministic and stochastic models on the subject are available in the literature. Most of the models have appeared with the need and requirement of a Just-in-Time (JIT) system environment. The close tie between a vendor and a buyer helps to deliver products in a shorter lead time with reduced inventory cost. Based on this idea, recently, some researchers have presented such a stochastic model with equal sized batch (part of a lot) transfer under controllable lead time. They have shown that their model provides a lower total cost for a numerical problem. To enrich the JIT system literature, considering transportation cost of a batch, this article develops an alternative model of the problem with equal or unequal sized batches transfer under controllable lead time. Then it develops a heuristic solution technique of the model and applying it solves the same numerical example to show a reasonable cost reduction.

Section: Introductionmentioning

confidence: 99%

An alternative model for integrated vendor–buyer inventory under controllable lead time and its heuristic solution

Hoque

2007

“…These decisions not only have cost implications, but equally determine the system's ability to respond to the customer. A range of contributions have been made in this field that have studied various combinations of demand and supply uncertainty (Rau, Wu, and Wee, 2004;Zequeira, Dura´n, and Gutie´rrez 2005;Arda and Hennet 2006), while the wider supply chain management debate commonly relates to the role of inventory under two contradicting themes: the first notion has been derived from the implementation of lean manufacturing (Womack, Jones, and Roos 1990;Womack and Jones 1996), the second from an increasing focus on responsive, or agile, supply chain strategies (Naylor, Naim, and Berry 1999;Christopher 2000). While the former has defined inventory through a negative reputation as 'waste', where it is seen to be hiding problems and process deficiencies (Ohno 1988;Shingo 1989), the latter argues for a pro-active use of inventory in supply chains to respond to changes in demand.…”

Section: Introductionmentioning

confidence: 98%

On the link between inventory and responsiveness in multi-product supply chains

Reichhart

Framiñán

Holweg

2008

Manufacturing systems in many industries face the challenge of manufacturing products that are assembled from multi-variant components. Demand for these component variants is correlated, and often subjected to an overall capacity constraint (e.g. fixed production volumes in the final assembly plant). Therefore, the modelling of supply chain systems under multi-variant product conditions is conceptually difficult as the demands for the individual variants are not independent. Previous approaches to modelling supply chain systems have commonly dealt with this complication by either focusing on single-product multi-tier systems, or single-tier systems with multiple products. In this article, we propose a modelling approach capable of studying the responsiveness of multi-tier systems with correlated demands, which is used as the input for a simulation model. Based on the simulation outcomes, generic relationships between product variety, responsiveness and inventory levels in a supply chain system are derived; and a novel safety stock formula for such settings is developed.

“…In some papers, lead time was considered as variable and controllable, and it can be shortened by adding extra crashing cost; see Chang (2005), Zequeira, Duran, and Gutierrez (2005), Fei and Xuejun (2010), etc. This article will focus on the influence of the time-varying delivery on the systems' upstream production planning.…”

Section: Introductionmentioning

confidence: 99%

Integrated planning problem in supply chains with time-varying delivery

Wang

Liu

Ding

et al. 2011

We consider a serial supply chain consisting of a raw material supplier, a manufacturer, a distribution centre and a retailer in the presence of time-varying delivery between manufacturer facility and the retailer warehouse. Delivery time functions are developed based on practical data analysis and the cost models for both linear and non-linear delivery time functions are derived. Analytic solution for system with linear delivery times is derived and a search algorithm for system with non-linear delivery times is established. Finally, sensitivity analysis is made to help decision makers achieve a lower total cost in practice.