Most people picture route planning as finding the shortest path through a list of addresses. For a parcel carrier with flexible delivery times, that is close to right. For a food distributor, it usually is not. A restaurant that receives between 2 and 4 p.m. does not care that its delivery came by a shorter road at 11 a.m. What matters is when each stop happens, whether the driver can finish inside legal hours, and whether the product arrives in good condition. Distance still costs money, but it is one input, not the goal.

Why shortest distance is the wrong goal

A distance-only plan treats every stop as interchangeable and every hour of the day as the same. Neither is true. A few ways it goes wrong:

  • It ignores windows. The shortest loop might reach a school kitchen after its receiving hours close. The stop fails, the product rides back, and someone has to deliver it again.
  • It ignores traffic. Ten miles across town at 7 a.m. and the same ten miles at 4 p.m. are different trips. Drive time, not distance, decides when the driver arrives.
  • It ignores time at the stop. A stop with a loading dock and a receiver waiting is quick. A stop where the driver hand-trucks cases down a basement stair and waits for someone to check in the order is not. Time spent at stops can be a large share of a route day, and a distance-only plan does not see it at all.

Here is a simple example. Suppose plan A is 5 miles shorter than plan B, but plan A reaches a hospital with a 6 to 9 a.m. window at 9:20. If each mile costs $2.00 to drive, plan A saves $10.00 and fails a stop. Redelivering that order the next day costs a whole extra stop, plus an unhappy customer. Plan B is the better plan.

What a food distribution route should optimize

A better objective is: deliver every stop inside its window, within driver hours and truck capacity, using the fewest trucks and driver hours. Distance and fuel then follow from a sensible sequence. In practice, the constraints come in this order:

  1. Delivery windows. Hard windows first: hospitals, schools and chains with fixed receiving hours. Soft windows (a stated preference) second.
  2. Time at each stop. An estimate of how long each customer takes to receive. Start with a default and adjust it for the slow stops you already know about.
  3. Driver hours. If your drivers are covered by federal hours-of-service rules, those limits are hard constraints, and a short-haul exception exists for some local operations. Check FMCSA's hours-of-service rules for what applies to your trucks and drivers, then add your own break and overtime policy.
  4. Truck capacity. Pallet positions, weight and, for multi-temperature trucks, space in each zone. A route that fits by weight can still fail on pallet positions.
  5. Product condition. Long doors-open times and long rides are hard on chilled and frozen product. Where you can, keep sensitive drops away from the end of a long day, and load so the driver is not digging through the truck at every stop.
  6. Distance and drive time. Once the above are satisfied, a shorter route is a better route.

A daily planning workflow

Good route planning is a routine, not an event. A workable sequence for each delivery day:

  1. Close the order book. Use a firm cut-off time so you plan from confirmed orders, not a moving list.
  2. Start from your standing routes. Customers on standing orders who see the same driver on the same day are a stable base. Fit the day's other orders around them.
  3. Place the hard windows. Put fixed-window stops on routes that can reach them in time.
  4. Fill the rest by drive time. Add the flexible stops where they cost the least extra time.
  5. Check capacity and hours. Every route should fit its truck and finish with some slack for traffic and slow stops.
  6. Review as a dispatcher. Software proposes; a person who knows the customers checks it. A dispatcher knows the stop with no parking before 10 a.m. and the receiver who leaves early on Fridays.
  7. Load in reverse stop order. The last stop goes on first, so each drop is at the door when the driver opens it.

Stable routes vs fresh optimization

There is a real trade-off here. Re-optimizing every day from scratch can produce shorter plans on paper, but it moves customers between drivers and changes their arrival times. Customers often value the same driver at the same time more than you value a few saved minutes. Drivers who know their stops also work faster and make fewer mistakes.

A middle path is to keep fixed route templates for regular customers, let the planner fit the day's extra orders around them, and re-plan a template only when its numbers keep slipping.

Check the plan against what happened

A plan is only as good as its assumptions. Each week, compare planned and actual arrival times stop by stop. If one customer is late every week, its time at the stop is probably underestimated. If one route runs long every day, it has too many stops for the hours it has. Track on-time rate and route time alongside the other trucking KPIs, and feed what you learn back into the stop times and windows the planner uses.

For customers whose windows shape the whole plan, see how to enforce customer-specific delivery windows.

Where APFoodz fits

APFoodz routing and dispatch builds routes that fit your trucks and your customers' delivery windows.