Supply Chain Optimization in a Stochastic Environment
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The emerging field of supply-chain management has changed forever the way global businesses operate. By taking advantage of information technologies, supply-chain management attempts to coordinate all the companies in a supply chain in order to optimize their operation. One of the major challenges faced by real-world decision makers when trying to optimize the operation of supply chains is that normal business intuition has proven to be ineffective. In turn, the main reason for such ineffectiveness is the inherent complexity of supply chains due to the many unpredictable events that affect them. In order to help real world decision makers, the impact of economic and operational parameters must be understood when optimizing supply chain systems. To gain an understanding of these effects, this research simulates supply chains in two extreme production environments. Since the deterministic environment and the exponential environment are essentially a lower bound and an upper bound, respectively, of real world situations, this research provides clues about how real world supply chains behave. This shows that although the impact sometimes is intuitive, many times it is not. Through simulation, the supply chain dynamics of randomized demand and variable capacity were modeled. These results were then exhaustively searched in order to find the optimum scenarios, and the data from all cases were analyzed. After analyzing and interpreting the results, it was shown that the impact of the parameters were not always intuitive. Some of the major findings included the convergence of optimum cost, quantity, and reorder point along several dimensions, the induction of unique patterns for each parameter, and the optimal behavior between the lower and upper bounds sometimes being essentially the same. Based on the data, it is true that optimizing supply chain operations is difficult to accomplish with intuition and reasoning. Essentially, real world decision makers must know about the patterns and trends found in this study. Being aware of the identified convergence, patterns, and bounds will help businesses to adjust their supply chains to improve performance. Further research is recommended to expand the scope of this study as well as for businesses to apply this research methodology to better understand supply chain optimization.
SubjectSupply Chain Management
Chiu, Sherwin S (2013). Supply Chain Optimization in a Stochastic Environment. Honors and Undergraduate Research. Available electronically from