Explore the vast range of titles available.

The last decades have seen a tremendous amount of research being devoted to effectively managing vehicle fleets and minimizing empty mileage. However, in contrast to, e.g., the air transport sector, the question of how to best assign crews to vehicles, has received very little attention in the road transport sector. The vast majority of road freight transport in Europe is conducted by single drivers and team driving is often only conducted if there are special circumstances, e.g., security concerns. While it is clear that transport companies want to avoid the costs related to additional drivers, vehicles manned by a single driver sit unused whenever the driver takes a mandatory break or rest. Team drivers, on the other hand, can travel a much greater distance in the same amount of time, because mandatory breaks and rests are required less frequently. This paper investigates under which conditions trucking companies should use single or team driving to maximize their profitability. We present a novel optimization approach for simultaneously optimizing routes and crewing decisions and provide experimental evidence that, for a wide range of cost factors, operating a fleet with a mix of team and single drivers can significantly reduce operational costs when compared to typical profit margins in the sector.

In most developed countries working hours of truck drivers are constrained by hours of service regulations. When optimizing vehicle routes, trucking companies must consider these constraints to assure that drivers can comply with the regulations. This paper studies the combined vehicle routing and truck driver scheduling problem (VRTDSP), which generalizes the well-known vehicle routing problem with time windows by considering working hour constraints. A branch-and-price algorithm for solving the VRTDSP is presented. This is the first algorithm that solves the VRTDSP to proven optimality.

Regulations regarding drivers' working hours often have a big impact on total transit times, i.e., the time required for driving periods, breaks, and rest periods. Although of particular importance for many real-life applications, they have received only very little attention in the vehicle routing literature. This paper describes the new regulations for drivers' working hours in the European Union that entered into force in April 2007. According to the new regulations, motor carriers must organise the work of drivers in such a way that drivers are able to comply with the respective regulations and are made liable for infringements committed by the drivers. This paper shows how motor carriers can schedule driving periods, breaks, rest periods, and handling activities, and presents a large neighbourhood search algorithm capable of generating vehicle tours complying with the new regulations.

Since April 2007 working hours of truck drivers in the European Union are controlled by regulation (EC) No. 561/2006. According to the new regulation, road transport undertakings must organise the work of drivers in a way that drivers are able to comply with the regulations and can be made liable for infringements committed by the drivers. Although of particular importance in long-distance haulage, regulations on working hours of truck drivers have received very little attention in the scheduling literature. This paper presents a method for scheduling driving and working hours of truck drivers with respect to regulation (EC) No. 561/2006. Given a sequence of locations to be visited within specified time windows, the approach is guaranteed to find a schedule complying with the regulation if such a schedule exists.

The U.S. truck driver scheduling problem (US-TDSP) is the problem of visiting a sequence of λ locations within given time windows in such a way that driving and working activities of truck drivers comply with U.S. hours-of-service regulations. In the case of single time windows it is known that the US-TDSP can be solved in O ( λ 3 ) time. In this paper, we present a scheduling method for the US-TDSP that solves the single time window problem in O ( λ 2 ) time. We show that in the case of multiple time windows the same complexity can be achieved if the gap between subsequent time windows is at least 10 hours. This situation occurs, for example, if, because of opening hours of docks, handling operations can only be performed between 8.00 a.m. and 10.00 p.m. Furthermore, we empirically show that for a wide range of other problem instances the computational effort is not much higher if multiple time windows are considered.

Transport companies seek to maximise vehicle utilisation and minimise labour costs. Both goals can be achieved if the time required to fulfil a sequence of transportation tasks is minimised. However, if schedule durations are too short drivers may not have enough time for recuperation and road safety is impaired. In Australia transport companies must ensure that truck drivers can comply with Australian Heavy Vehicle Driver Fatigue Law and schedules must give enough time for drivers to take the amount of rest required by the regulation. This paper shows how transport companies can minimise the duration of truck driver schedules complying with Australian Heavy Vehicle Driver Fatigue Law. A mixed integer programming formulation is presented and valid inequalities are given. Computational experiments show that these inequalities provide significant reduction in computational effort when using one of the most advanced commercial mixed integer programming solver.

Driver fatigue is internationally recognized as a significant factor in approximately 15%-20% of commercial road transport crashes. In their efforts to increase road safety and improve working conditions of truck drivers, governments worldwide are enforcing stricter limits on the amount of working and driving time without rest. This paper describes an effective optimization algorithm for minimizing transportation costs for a fleet of vehicles considering business hours of customers and hours of service regulations. The algorithm combines the exploration capacities of population-based metaheuristics, the quick improvement abilities of local search, with forward labeling procedures for checking compliance with complex hours of service regulations. Several speed-up techniques are proposed to achieve an overall efficient approach. The proposed approach is used to assess the impact of different hours of service regulations from a carrier-centric point of view. Extensive computational experiments for various sets of regulations in the United States, Canada, the European Union, and Australia are conducted to provide an international assessment of the impact of different rules on transportation costs and accident risks. Our experiments demonstrate that European Union rules lead to the highest safety, whereas Canadian regulations are the most competitive in terms of economic efficiency. Australian regulations appear to have unnecessarily high risk rates with respect to operating costs. The recent rule change in the United States reduces accident risk rates with a moderate increase in operating costs.

As resources are valuable assets, organizations have to decide which resources to allocate to business process tasks in a way that the process is executed not only effectively but also efficiently. Traditional role-based resource allocation leads to effective process executions, since each task is performed by a resource that has the required skills and competencies to do so. However, the resulting allocations are typically not as efficient as they could be, since optimization techniques have yet to find their way in traditional business process management scenarios. On the other hand, operations research provides a rich set of analytical methods for supporting problem-specific decisions on resource allocation. This paper provides a novel framework for creating transparency on existing tasks and resources, supporting individualized allocations for each activity in a process, and the possibility to integrate problem-specific analytical methods of the operations research domain. To validate the framework, the paper reports on the design and prototypical implementation of a software architecture, which extends a traditional process engine with a dedicated resource management component. This component allows us to define specific resource allocation problems at design time, and it also facilitates optimized resource allocation at run time. The framework is evaluated using a real-world parcel delivery process. The evaluation shows that the quality of the allocation results increase significantly with a technique from operations research in contrast to the traditional applied rule-based approach.

This paper studies the problem of scheduling working hours of team drivers in European road freight transport where a sequence of λ locations must be visited within given time windows. Since April 2007 working hours of truck drivers in the European Union must comply with regulation (EC) No 561/2006. These regulations impose standard limits on the daily driving times of truck drivers and extended daily limits that may only be used twice a week for each driver. We present a depth-first-breadth-second search method which can find a feasible schedule complying with standard daily driving time limits in O (λ 2 ) time, if such a schedule exists. Furthermore, we show that this method can also be used to find schedules complying with regulation (EC) No 561/2006 if daily driving times may exceed the standard limit.

This paper presents and studies the Canadian Truck Driver Scheduling Problem (CAN-TDSP), which is the problem of determining whether a sequence of locations can be visited within given time windows in such a way that driving and working activities of truck drivers comply with Canadian Commercial Vehicle Drivers Hours of Service Regulations. Canadian regulations comprise the provisions found in US hours of service regulations as well as additional constraints on the maximum amount of driving and the minimum amount of off-duty time on each day. We present two heuristics and an exact approach for solving the CAN-TDSP. Computational experiments demonstrate the effectiveness of our approaches and indicate that Canadian regulations are significantly more permissive than US hours of service regulations.