CENTRALIZED AND DECENTRALIZED DISTRIBUTION STORAGE SYSTEMS

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.

Autorentext
Tomasz M. Kosalka, MS: Studied Industrial Engineering at West Virginia University, Senior Analyst at Progressive Insurance Inc., Hudson, OH.

Klappentext
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.