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

Overview: Introduction Background Objective Approach Results & Discussion Conclusion

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

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

Background First change in 60 years

Objective 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

Approach 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

Demand Generation 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

Capacity Management 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

Load and Tractor Assignment 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

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

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

Runtime Environment 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

Results and Discussion 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 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 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 HOS changes Marginal improvement at 70 MPH over 62 MPH Conclusion:

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

Conclusion 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 The Business:

Evaluating Real World Results 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? 1 st 5 Months of 2004

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