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Wave Planning & Multi-Trip Routes

Wave Planning Diagram

Maximizing Fleet Utilization with Double Runs​

Wave Planning (or Multi-Trip routing) represents the operational strategy where a single vehicle performs multiple distinct delivery loops in a single shift. Instead of a truck sitting idle after completing a 4-hour morning run, it returns to the depot, reloads, and executes a second (or third) "wave" of deliveries.

This strategy is critical for increasing asset utilization—getting more value out of every truck and driver on the road.

Industries & Use Cases​

  1. Urban Last-Mile Delivery:
    • Scenario: E-commerce or courier vehicles with small capacity but short distances. A van might depart at 08:00, deliver 50 packages, return to the hub at 12:00, reload, and depart again at 13:00.
    • Goal: Minimize the fleet size required to cover daily volume.
  2. Bakery & Fresh Food:
    • Scenario: Morning wave delivers fresh bread (must be at stores by 07:00). Second wave collects returns/empties or delivers ambient products with less critical deadlines.
    • Goal: Meet strict morning time windows without purchasing a massive fleet that sits idle for the rest of the day.
  3. Beverage Distribution:
    • Scenario: Heavy loads mean trucks hit weight capacity quickly. They "weigh out" before they "time out," requiring a return to the warehouse to restock.

The Optimization Challenge​

Manual planning for multi-trip routes is significantly harder than standard routing because of the "interdependencies" between trips:

  • Time Synchronization: Trip A must finish and allow reload time before Trip B can start.
  • Depot Capacity: You cannot have your entire fleet return to the reload docks at the exact same minute; dock slots are limited.
  • Driver Hours: Total shift time must respect legal driving limits, summing up the drive time of all waves plus reload times.

Modeling with the API​

Our optimization engine treats multi-trip routing as a first-class citizen, allowing you to define route quality constraints and reload rules explicitly.

1. Enabling Multi-Trip Logic​

To allow a vehicle to perform multiple trips, you don't need complex workarounds. You simply need to ensure your constraints allow for it.

Key Concept: Reload Stops A vehicle completes a trip when it visits a location designated as a "Reload" point (usually the depot) or concludes its route. The solver automatically decides if a return to the depot is efficient.

For detailed implementation guidance, refer to the Trip Stops Documentation.

2. Controlling Wave Duration​

Often, you want to enforce that no single "wave" is too long (e.g., to keep food frozen), or that the driver takes a break between waves.

  • Max Trip Duration: Limits the length of any single loop from depot to depot.
  • Max Route Duration: Limits the total shift length (Trip 1 + Reload + Trip 2).

For detailed implementation guidance, refer to the Max Trip Duration Documentation.

3. Balancing Costs & Utilization​

You can guide the solver to prefer multi-trip routes over hiring new vehicles by adjusting cost parameters.

  • Fixed Cost: High fixed costs for using a vehicle encourage the solver to reuse existing vehicles (Wave 2) rather than activating a new one.
  • Trip Cost: You can assign a specific "cost per trip" to penalize excessive reloading if you prefer fewer, longer routes.

For detailed implementation guidance, refer to the Trip Cost Documentation.

By configuring these parameters, you turn a static fleet into a dynamic circulation system, drastically reducing the number of vehicles needed to service high-volume operations.

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