Simulation Analysis of Truck Driver Scheduling Rules

1. Simulation Analysis of Truck Driver Scheduling Rules Eric C. Ervin Russell C. Harris J.B. Hunt Transport, Inc. 615 J.B. Hunt Corporate Drive P.O. Box 130 Lowell, Arkansas 72745, U.S.A. Presented By: Craig Rachel, Midwestern State University

2. Introduction • Background • Objective • Approach • Results & Discussion • Conclusion Overview:

3. Redefined Employee Workday • Modified Planning Process • Productivity Changes that will influence the profitability of customer contracts Change in regulations on hours of service (HOS) for truck drivers • 120,000 unique freight lanes • 5,000 tractors • 10,000 trailers Impacts of Implementation of Scheduling Changes Introduction

4. Order-to-Delivery Process • Truck Driver’s daily routine Modeling of Two Important Aspects To show interaction and flow of • People • Equipment • Material • Information Introduction

5. First change in 60 years Background

6. Determine the impact of the new 2004 HOS rules as they apply to driver utilization, customer on-time service and the nature of the company’s freight network • Develop a strategy to mitigate any negative impact on utilization and efficiency Objective

7. Demand Generation • Capacity Management • Load and Tractor Assignment • Driver Log Management • Transportation Execution • Customer Freight Pick-up and Delivery Six (6) Major Processes Modeled in the Simulation Approach

8. Generated over 12 month period • Represented data extracted from 1 full year of actual history • Reflected seasonality • Demand that was not accommodated due to lack of capacity waited up to 24 hours Demand Generation

9. Capacity = Driver • On dispatch (in service), not on dispatch (available), at home (until completion of off-duty time) • Derived from data collected at company warehouses Capacity Management

10. Maximize efficiency • Minimize empty miles • Avoid customer service failures • Avoid assigning loads to drivers who were due home soon • Preference giving to drivers based on how close to the load they were • Driver needed sufficient hours Load and Tractor Assignment

11. Company load history characteristics were used • Assumes average velocity rises as trip continues • Consider congestion urban areas and assume longer trips utilize expressways Transportation Execution

12. Off-duty, general off-duty • Off-duty, driver in sleeper berth or at home • On-duty, driving • On-duty, not driving. Loading/unloading Driver Logs

13. 2 GHZ CPU, 1 GB RAM • Single Replication took 4 hours on average • Experiments took 4 replications or 16 hours to complete • Simulated the system for 1 year Runtime Environment

14. 10 hours vs. 11 hours driving per shift • 15 hours vs. 14 hours on duty per shift • 8 hours vs. 10 hours break time between shifts • The non-consecutive vs. consecutive nature of on duty time Analysis of results focused on key differences implemented in 2004: Results and Discussion

15. Only 3 hours in 14 hour work window to cover inspections, fueling, and loading & unloading • Any delays, erodes the 11 hours available to drive Biggest Finding: Impact of Consecutive Nature of the way on-duty time is logged Results and Discussion

16. Speed limit of 62 MPH • Speed limit of 65 MPH • Speed limit of 68 MPH • Speed limit of 70 MPH Baseline 2003 (old scenario) vs. 2004 HOS changes Conclusion: Marginal improvement at 70 MPH over 62 MPH Results and Discussion

17. Expect miles to drop 2-3% • Amount of time to deliver load will go up • MPH increase only marginally improves productivity Communicate to Drivers: Conclusion

18. Conclusion Communicate to Customers: • Service level impact – decrease 2.4% • Evaluate special fees for customers

19. Conclusion The Business: • Develop a pricing strategy that factors in loss of miles, etc • Prepare for potential capacity decrease • Optimize the 3 hours that drivers have for inspections, etc • Consider the 14 hour work window when determining how to dispatch drivers

20. Evaluating Real World Results 1st 5 Months of 2004 • Industry given grace period in 2004 • Utilization is up in 2004, not comparing the same numbers • Company policy changed, how did this effect the numbers?

21. References Jain, S., R.W. Workman, L.M. Collins, E.C. Ervin and A.P. Lathrop, 2001. Development of a High Level Supply Chain Simulation Model Law, Averill M. and W. David Kelton, 1991. Simulation Modeling & Analysis, 2nd Edition, McGraw-Hill, Inc. USA. Taylor, G. Don, T.S. Meinert, R.C. Killian and G.L. Whicker, 1999. Development and Analysis of Alternative Dispatching Methods in Truckload Trucking.