Global Supply Chain - Uniformly Random Logistics Data from a Caterpillar's Test Case

Caterpillar Inc. is the world leader in manufacturing of construction and mining equipment, diesel and natural gas engines, industrial gas turbines and diesel-electric locomotives. The current revenue of Caterpillar is on the order of tens of billions and they sell products and parts via a worldwide dealer network. Caterpillar sells more than 3 million products and 700,000 parts in more than 20 countries around the world every year. They operate with more than 3,000 suppliers and 3,000 dealerships and their logistics operations alone are worth more than 60 million dollars per year. The dataset provided is one example of supply chain problem for one product of Caterpillar - a medium size excavator. In the current dataset, the number of dealers, production facilities and shipping ports is the same as in the original problem; it is only the demand figures, the production capacities, the transportation times and costs and the sale prices that have been randomly generated. The figures have been generated according to a normal distribution with the same mean and standard deviation as in the original dataset (e.g. the demand figures have the same mean and standard deviation as those found in the original problem).