A case study has been uploaded to Canvas under Module 3: Simao et al, Approximate Dynamic Programming Captures Fleet Operations for Schneider National, Interfaces, Vol 40, No 5, pages 342-352, 2010. This paper presents a case study on scheduling trucks/drivers. Please read the papers multiple times (in particular Introduction, The Operational Problem, and The Optimization Challenge) and answer the following questions.

1: Is this case study for less-than-truck-load or truck-load?

2: What are major driver attributes that need to be considered?

3: Before using an optimization tool, the decisions are made by the dispatchers at Schneider National. What are the major factors the dispatchers consider when making a decision?

4: In the lecture, we discussed a truck-load scheduling application of a logistic company. The time horizon for decision-making of that application is 2 days. What about the time horizon in this study?

5: There is only one depot, where the vehicles start from and return to in the examples we discussed during class. What about in this case study? Can you provide a rough estimation on the number of depots?

6: The underlying network and mixed-integer linear programming model we discussed for truck-load scheduling of the logistic company are actually the approaches of time-space network as seen in Figure 2, page 345. What are the weaknesses of such an approach for this case study? List at least two.

7: Based on your understanding, what are the major difficulties for this case study?