The design of a Supply Chain network has a great impact on a company’s performance. Simulation modeling and optimization techniques were selected to analyze and solve supply chain and distribution storage problems. The techniques were applied to a decision making process of reconfiguring an existing distribution storage system, and modifying it from centralized to a decentralized one. This research presented a methodology for identifying data needs, building an analytical database, creating simulation models with Arena software, optimizing the models with OptQuest software, and performing sensitivity analysis. As a result of applying this methodology, it was found that the centralized distribution storage system allows the company to operate at a lower cost (savings from 11.03% to 19.09%) while providing customers with better service. The sensitivity analysis proved that savings are affected by transportation cost, demand volume, and the time at which products need to be available for delivery. Simulation/optimization approach was found to be effective and allowed for the creation of a methodology that can be repeated for similar types of problems.

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