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Trip cost

In the Vehicle Routing Problem (VRP), the concept of "trip cost" is used to model the cost or penalty associated with a vehicle making a trip to serve a specific order. This cost can represent various factors, such as the distance traveled, the time spent, or other operational expenses. By assigning a trip cost to each order, the optimization algorithm can prioritize routes that minimize these costs, leading to more efficient and cost-effective solutions.

Impact on Route Planning:

Trip cost significantly influences route planning in the VRP. The optimization algorithm aims to minimize the total trip cost across all vehicles and orders. This often leads to:

  • Prioritizing Shorter Trips: Routes with shorter distances or travel times are preferred, as they incur lower trip costs.
  • Clustering Orders: Orders that are geographically close to each other are more likely to be served by the same vehicle, as this reduces the overall trip cost.
  • Balancing Trip Costs: The algorithm seeks to balance the trip costs across all vehicles, avoiding situations where some vehicles have very high trip costs while others have very low costs.
  • Trade-offs with Other Constraints: Trip cost is considered alongside other constraints, such as vehicle capacity, time windows, and driver availability. The algorithm must find a solution that balances these competing factors.

Trip Cost in PDP Mode:

In PDP (Pick-up and Delivery Problem) mode, the cost of a trip influences subsequent travel decisions. High trip costs cause the optimization engine to prioritize dropping off existing passengers earlier, even if it means foregoing other potential pickups. Conversely, lower trip costs lead the algorithm to prioritize picking up more passengers or goods. This prioritization, driven by trip cost, can significantly affect service quality, potentially resulting in longer passenger wait times to optimize overall route efficiency.

Implementation in SWAT APIs​

In SWEAT APIs trip cost is controlled by trip_cost parameter that can be set for each booking or at a simulation level. It is also supported in Optimization API