Moltline Optimize

Order up to 12 stops into the shortest single-vehicle route on your distance matrix. FREE. Typical input {"stops": [{"id": "depot"}, {"id": "A"}, {"id": "B"}], "matrix": [[0, 5, 9], [5, 0, 4], [9, 4, 0]]} returns {"routes": [{"vehicle": 0, "stops": [...], "distance": 18.0}], "total_distance": 18.0, "solver_status": "FEASIBLE", "note": "..."}. The matrix is in your units (km, minutes, cost) and mu

Capacitated, time-windowed routing for a fleet over up to 200 stops. PREMIUM (license). Typical input {"stops": [{"id": "depot", "window": [480, 1080]}, {"id": "A", "demand": 3, "window": [540, 720], "service_min": 10}, ...], "matrix": [[...]], "vehicles": [{"id": "van1", "capacity": 10}, {"id": "van2", "capacity": 8, "max_distance": 120}]} returns {"routes": [{"vehicle": "van1", "stops": [{"id":

Straight-line (great-circle) distance matrix from coordinates. FREE. Typical input {"points": [{"id": "depot", "lat": 51.5, "lon": -0.12}, {"id": "A", "lat": 51.52, "lon": -0.1}]} returns {"matrix": [[0, 2.6], [2.6, 0]], "unit": "km", "kind": "straight-line (haversine), not road distance"}. Use when you have no road matrix and a straight-line approximation is acceptable, or to sanity-check one. N

Place up to 20 boxes into containers or pallets with rotation, weight and support rules. FREE. Typical input {"items": [{"id": "A", "l": 60, "w": 40, "h": 30, "weight": 12, "qty": 4}], "containers": [{"id": "pallet", "l": 120, "w": 80, "h": 150, "max_weight": 500, "qty": 2}]} returns {"containers_used": 1, "containers": [{"placements": [{"id": "A", "x": 0, "y": 0, "z": 0, "l": 60, "w": 40, "h": 3

Same packer as pack_bins for up to 300 item units and 200 containers. PREMIUM (license). Typical input {"items": [{"id": "SKU1", "l": 40, "w": 30, "h": 20, "weight": 5, "qty": 120}, ...], "containers": [{"id": "euro-pallet", "l": 120, "w": 80, "h": 180, "max_weight": 800, "qty": 10}]} returns the same shape as pack_bins: containers with placements, fill percentages, weights and any unplaced units

Least-waste cut plan for bars, pipes or boards from stock lengths, with saw kerf. FREE. Typical input {"stock": [{"length": 6000, "cost": 30}], "parts": [{"length": 2200, "qty": 3}, {"length": 1500, "qty": 4}], "kerf": 3} returns {"bars": [{"stock_length": 6000, "cuts": [2200, 2200, 1500], "waste": 94}], "bars_used": 3, "waste_pct": 4.2, "solver_status": "OPTIMAL"}. Minimises total stock cost (or

Guillotine cut layouts for rectangular parts from sheets, with kerf and grain. PREMIUM (license). Typical input {"sheets": [{"id": "ply", "l": 2440, "w": 1220, "qty": 5}], "parts": [{"id": "side", "l": 800, "w": 400, "qty": 6}], "kerf": 3} returns {"sheets_used": 1, "layouts": [{"sheet": "ply", "placements": [{"id": "side", "x": 0, "y": 0, "l": 800, "w": 400, "rotated": false}], "fill_pct": 64.5,

Assign staff to shifts under availability, skills, hour caps and rest gaps. PREMIUM (license). Typical input {"staff": [{"id": "ana", "skills": ["till"], "max_hours": 40, "unavailable": ["sat-am"]}, ...], "shifts": [{"id": "sat-am", "start": "2026-09-12T08:00", "end": "2026-09-12T14:00", "required": 2, "skill": "till"}, ...], "rules": {"min_rest_hours": 11, "max_consecutive_days": 6}} returns {"a

Choose the items that maximise value under one or more capacity limits. FREE. Typical input {"items": [{"id": "a", "value": 60, "weight": 10, "cost": 120}, {"id": "b", "value": 100, "weight": 20, "cost": 300}], "limits": {"weight": 25, "cost": 400}} returns {"selected": ["a"], "value": 60, "used": {"weight": 10, "cost": 120}, "slack": {"weight": 15, "cost": 280}, "solver_status": "OPTIMAL"}. Any

Check a problem's shape and obvious feasibility before spending solver time. FREE. Typical input {"type": "route", "problem": {"stops": [...], "matrix": [[...]], "vehicles": [...]}} returns {"ok": false, "issues": ["total demand 34 exceeds total capacity 30"], "size": {"stops": 14, "vehicles": 2}, "tier_hint": "route_plan_fleet (licence) - more than 12 stops"}. Types: route, pack, cut1d, cut2d, r

Plain-language summary of a solution from this server and the constraints that bind. FREE. Typical input {"solution": <result of route_plan_fleet>} returns {"summary": "2 vehicles serve 14 stops over 96.4 km; 1 stop unserved", "binding_constraints": ["van2 is at 100% of capacity", "stop C arrives at the end of its window"], "status": "FEASIBLE"}. It recognises results from route_plan, route_plan_