This artifact is similar to pouring champagne for friends at a party. As you try to fill each glass equally, you often end up with one glass that’s not entirely filled. Similarly, a computer’s objective is to load all shipments while minimizing the number of vehicles, filling some vehicles to capacity while leaving a residual load for a partially used vehicle.
Dispatchers often expect balanced workloads across all vehicles. However, an optimal algorithm will have already accounted for various factors like distance and vehicle use. Attempting to balance workloads for aesthetic reasons may increase the overall cost of the solution. Remainder tours naturally occur when capacity is the main constraint, and shipments are relatively small compared to vehicle capacity. When time or other factors limit the solution, capacity is more evenly distributed. With bulkier shipments, loading distribution is already high.
Using a planning model, this artifact can be mitigated by introducing controlled overtime. Instead of distributing work evenly across all vehicles, the algorithm prioritizes maximizing the utilization of each driver’s regular working time before assigning additional resources. Only when necessary does it extend into overtime, thereby reducing the need for partially utilized vehicles while still maintaining overall efficiency.
Using a planning model, this artifact can be mitigated by introducing controlled overtime. Instead of distributing work evenly across all vehicles, the algorithm prioritizes maximizing the utilization of each driver’s regular working time before assigning additional resources. Only when necessary does it extend into overtime, thereby reducing the need for partially utilized vehicles while still maintaining overall efficiency.
Create balanced tours in NUNAV Courier
In NUNAV Courier applications, this behavior can be influenced directly through driver settings. By adjusting work time and overtime parameters, planners can shape how the algorithm distributes workload. A practical approach is to set the regular work time deliberately lower, reflecting the desired average workload across the fleet, and then allow sufficient overtime to cover a full working day. This encourages the system to concentrate work on fewer vehicles before opening additional tours, leading to more balanced and cost-efficient results.
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