Scheduled pickup and dropoff, route persistence across the week, and turnaround SLAs handled.
Laundry is one of the most schedule-dense home-services verticals. A single customer is on your route twice — once for pickup, once for dropoff 24 or 48 hours later — and the operational unit is not the day, it's the week. The right tool needs to optimize a recurring weekly route, respect customer-chosen 1- or 2-hour pickup windows, and handle the dropoff side as a separate but linked stop. SortDrops handles each of these.
Laundry is the only common last-mile vertical where the same customer appears on the route twice in one week as a single business event. A pickup on Monday creates a guaranteed dropoff on Wednesday or Thursday. Most route planners treat these as independent stops — SortDrops Pro lets you pair pickup-dropoff with a service-time link, so cancelling the pickup automatically cancels the linked dropoff, and rescheduling the pickup propagates the new dropoff date.
Customer-chosen time windows dominate the planning. Most laundry customers book a 1- or 2-hour window (e.g., 'pickup between 10:00 and 12:00 on Monday'). The optimizer must respect these windows, not just minimize distance. SortDrops Team supports per-stop time windows, and the optimizer treats out-of-window arrivals as a hard constraint, not a soft preference.
Weekly route persistence: a high-quality laundry fleet runs the same route Monday-Friday, picking up new customers and dropping off finished orders on roughly the same daily loop. The driver memorizes the loop. SortDrops supports route templates — save Monday's optimized route as a template and re-instantiate it next Monday with the new stop set, so the driver sees a familiar shape with new addresses interleaved.
A typical mid-sized laundry day: dispatcher arrives 07:00, imports today's pickup list (40–80 stops) and today's dropoff list (40–80 stops, paired to pickups from 48 hours ago), runs SortDrops dispatch in mixed pickup-dropoff mode, and assigns to 4–8 drivers. Each driver gets a route that mixes pickups and dropoffs in the geographically optimal order, so a driver might pick up from villa A, drop off at villa B 200 metres later, pick up from villa C 400 metres after that — all in one continuous loop.
Time windows make the optimization stricter than ordinary courier work. A 1-hour customer window plus a 5-minute pickup-bag-tagging service time means each driver can only do ~10 windowed stops per hour at best, and realistic dense urban delivery is 6–8 windowed stops per hour. SortDrops respects the math and won't over-promise.
End of day, the dispatcher tags the picked-up bags into the wash queue (most laundries do this in a separate bag-tracking system) and SortDrops marks the pickup stops complete. Dropoff stops for those same bags will appear automatically on the day-after-tomorrow route.
Pickup-dropoff pairing is a SortDrops Pro feature: a pickup stop has an attached return-stop reference, so cancelling, rescheduling, or moving the pickup automatically affects the linked dropoff. This eliminates the most common laundry-routing error — pickup gets cancelled but the dropoff still appears on the route two days later.
Route templates: save a high-frequency optimized route as a template (e.g., 'Tuesday morning Jumeirah loop') and re-use it next Tuesday with the new customer set. The optimizer fits new stops into the template shape rather than rebuilding from scratch, so the driver experience stays consistent week-to-week.
Yes. The optimizer treats pickups and dropoffs as the same routing primitive (a stop with a type) and orders them in the geographically optimal sequence. A driver can pick up at villa A, drop off at villa B nearby, pick up at villa C, all on one loop.
On Pro, a pickup stop carries a reference to its eventual dropoff. If you cancel the pickup, the dropoff is automatically cancelled. If you move the pickup, the dropoff date moves accordingly. This eliminates the orphan-dropoff problem that plagues most laundry fleets.
Yes — Pro feature. Save the optimized route as a template and re-instantiate next Monday with new stops. The optimizer fits new stops into the template shape, preserving the driver's familiar loop pattern.
Yes — Team feature. Per-stop time windows are a hard constraint in the optimizer, so a stop with a 10:00–11:00 window will not be ordered such that the projected arrival is 11:30. If the windows make the route infeasible, the optimizer flags it before dispatch.