Building a model-based decision support system for solving vehicle routing and driver scheduling problems under hours of service regulations.

Min, Hokey · 2011 · ROSA P / University Transportation Centers Program (U.S.)

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Summary

This paper addresses the operational challenges faced by regional common carriers in complying with the Federal Motor Carrier Safety Administration’s (FMCSA) 2005 Hours of Service (HOS) regulations. These regulations, designed to mitigate driver fatigue—a leading cause of truck accidents—restrict consecutive driving hours and mandate extended off-duty periods. Compliance imposes significant costs on the trucking industry, including potential labor shortages and fines, while complicating the simultaneous scheduling of drivers and vehicles. The authors propose a model-based Decision Support System (DSS) to help dispatchers optimize vehicle routes and driver schedules under these constraints, aiming to minimize total tour time and transportation costs while ensuring regulatory compliance. The proposed DSS integrates three components: a Relational Database Management System (RDBMS) for storing temporal, traffic, work schedule, and regulatory data; a Model Management Subsystem featuring a Mixed-Integer Programming (MIP) model and Geographic Information System (GIS) for visualization; and a Dialogue Management Subsystem for "what-if" scenario analysis. The core mathematical model addresses the Combined Time-Dependent Vehicle Routing and Driver Scheduling Problem under HOS regulations (CTRDSP-HOS). It minimizes total tour time, including travel, waiting, service, and break times, subject to time windows and HOS constraints. To handle the problem's combinatorial complexity, the authors developed a two-phase solution procedure. The initialization phase uses a greedy heuristic combined with a modified Dijkstra’s algorithm (TDD-HOS) that accounts for time-dependent vehicle speeds and mandatory rest breaks. The improvement phase employs a Simulated Annealing (SA) meta-heuristic to refine the initial tour. The system was validated through application to a real-world problem involving a regional common carrier in the United States. The model successfully coordinated driver and vehicle schedules, incorporating variable traffic speeds and strict HOS rules, such as the 11-hour driving limit and 10-hour off-duty requirement. The integration of GIS and RDBMS allowed for efficient data handling and spatial visualization of routes and logistics infrastructure. The results demonstrated that the DSS could generate feasible, near-optimal schedules that minimize driver waiting times and avoid early or late arrivals, effectively balancing cost efficiency with regulatory compliance. The significance of this work lies in its comprehensive approach to integrating complex regulatory constraints with time-dependent routing models. Unlike prior studies that often treated vehicle routing and driver scheduling separately or assumed constant vehicle speeds, this DSS simultaneously optimizes both elements while accounting for real-world variables like traffic congestion and changing HOS rules. The system provides trucking firms with a practical tool for contingency planning and cost control, offering a robust solution to the scheduling nightmares created by the intersection of driver safety regulations and operational efficiency demands.

Key finding

A model-based decision support system integrating mixed-integer programming and simulated annealing successfully generates compliant driver schedules and truck routes that minimize total tour time under complex Hours of Service regulations.

Methodology

modeling

Provenance

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Topics

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• hours of service