Combining MPC and LD Analysis in Supply Chain Inventory Control Problem

Author(s):  
Paris Pennesi
Author(s):  
Banu Yetkin Ekren ◽  
Bartu Arslan

Since it affects the performance of whole supply chain significantly, definition of correct inventory control policy in a supply chain is critical. Recent technological development enabled real time visibility of a supply network by horizontal integration of each node in a supply network. By this opportunity, inventory sharing among stocking locations is also possible in the effort of cost minimization in supply chain management.  Hence, lateral transshipment gained popularity and studies seeking the best lateral-transshipment policy is still under research. In this study, we aim to compare different lateral-transshipment policies for an s, S inventory control problem for a single-echelon supply chain network system. In this work, we consider a supply network with three stocking locations which may perform lateral transshipment among them when backorder takes place. We develop the simulation models of the systems in ARENA 14.5 commercial software and compare the performance of the policies by minimizing the total cost under a pre-defined fill rate constraint by using an optimization tool, OptQuest, integrated in that software. The results show that lateral transshipment works well compared to the scenario when there is no lateral transshipment policy in the network.


2011 ◽  
Vol 411 ◽  
pp. 378-382
Author(s):  
Yong Gao ◽  
Ming Yu Li ◽  
Jian Ping Wang

In order to resolve material ordering and inventory control problem in supply chain, optimization method based on GA is put forward. Supply chain model in the paper is made up of one supplier, one manufacturer, N-retailers and end customers. Moreover, supply chain model is developed in terms of two policies: traditionally centralized controlling policy and the coordinating controlling policy. Lastly, optimizing ordering and inventory control problem for supply chain is solved by genetic algorithm (GA), and an instance is illustrated to show the validity of the method.


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