Automate and optimize warehouse order picking
Every warehouse has a WMS that releases the order lines for the next wave. Most then rely on fixed pick-path rules, and decide who picks each line, in what order, and when to drop off a full cart as separate steps. Let's solve them as one problem.
One solve assigns every pick, sequences every route, and splits every trip
Timefold solves pick assignment, route sequencing, and cart trips as one optimization problem. Certified zones, equipment, one-way aisles, cart and lifting limits, shift and battery limits, carrier cut-offs, client separation, aisle capacity, and required FEFO rules are enforced as hard constraints, so every route can actually be walked. Within those rules, the model weighs travel time most heavily, followed by SLA lateness and overtime.
Where Timefold goes beyond pick-path heuristics
Four places where pick-path heuristics fall short. Timefold bakes each one into the model.
Cart trips are part of the route
When the cart is full, the route walks to the nearest drop-off and starts a new trip, all inside one plan.
Aisles don't clog up
Pickers are timed so no aisle holds more than it can take, and no two pickers reach for the same bin.
Late orders surface before the truck leaves
A pick no one can fit into the wave is flagged at planning time, so the shift lead can act before a cut-off is missed.
Work in progress stays put
Re-plan mid-wave and every pick already started stays where it is, while the model optimizes everything else.
Picking is the most expensive job in the warehouse
Order picking takes more labor than any other warehouse activity, and about half of every picker's time goes to walking between bins. Every extra meter on a route costs labor, and a slow wave turns into late orders and missed trucks.
Of warehouse operating cost goes to order picking
More than any other activity in the building.
Of picking time is spent traveling
Walking between bins is the biggest share of a picker's time, and it's the part a better route cuts.
Pick lines in a single shift
Spread across as many as 200 human pickers and AMRs, far too many to sequence by hand.
Lost when an order misses its carrier cut-off
Miss the truck by a minute and the order ships tomorrow, along with any SLA penalty.
Constraints the model expresses today
When scheduling works, everything works.
Less waste. More control. Teams that trust the plan.