The value of real time yield information in multi-stage inventory systems - Exact and heuristic approaches

We consider a random yield inventory system, where a company has access to real time information about the actual yield realizations. To contribute to a better understanding of the value of this information, we develop a mathematical model of the inventory system and derive structural properties. We build on these properties to develop an optimal solution approach that can be used to solve small to medium sized problems. To solve large problems, we develop two heuristics. We conduct numerical experiments to test the performances of our approaches and to identify conditions under which real time yield information is particularly beneficial. Our research provides the approaches that are necessary to implement inventory control policies that utilize real time yield information. The results can also be used to estimate the cost savings that can be achieved by using real time yield information. The cost savings can then be compared against the required investments to decide if such an investment is profitable. (C) 2014 Elsevier B.V. All rights reserved

The Value of Supply Chain Visibility when Yield is Random

This dissertation focuses on supply chains with uncertainty due to random yields. A common assumption in such systems is that the yields are observable only after all transportation or production steps are completed. The actual yield realization however happens earlier during the process. Technological advances and stronger supply chain collaboration make it possible to observe yield realization in real time and therefore close the time gap between the event and the observation. Within this thesis optimal and heuristic policies are developed that make use of this new type of information in various supply chain settings. These policies are used to identify conditions under which real time yield information is particularly beneficial