Warehouse Distribution Planner Calculator

Allocate orders across warehouses with clear constraints fast. Estimate cost, utilization, and unmet demand instantly. Export reports, test scenarios, and improve delivery performance daily.

Planner inputs

Enter warehouse capacity and costs, region demand, and distances. The tool assigns each region to the cheapest available warehouse capacity.

Used for display and downloads.
Costs are multiplied by this window.
USD
Distance-based variable shipping cost.
Applied to distance-based shipping only.
1.00 = normal, 1.15 = peak demand.
If set, overages can be penalized.
USD
Adds cost when distance exceeds max.

Warehouses (up to 4)

Name Capacity/day Fixed cost/day Handling cost/order
USD
USD
USD
USD
USD
USD
USD
USD

Regions (up to 5)

Name Demand/day (orders)

Distance matrix (km)

Provide straight-line or driving distance estimates. Only active warehouses and regions are used in the plan.

Warehouse \\ Region Metro A Metro B Metro C Metro D R5
Central DC
North Hub
South Hub
W4
Reset

Example data table

These sample values mirror the prefilled fields. Replace them with your own network and demand profile.

Warehouse Capacity/day Fixed/day Handling/order Regions and demand/day
Central DC 1200 1800 0.45 Metro A 850, Metro B 620, Metro C 410, Metro D 300
North Hub 700 1100 0.55 Distances vary per lane, set in matrix.
South Hub 650 1050 0.52 Use max distance and penalty only if needed.
Tip: If demand exceeds capacity, the calculator reports unmet demand per region.

Formula used

The planner assigns each region’s demand to warehouses by ascending variable cost per order, while respecting capacity.

  • Fuel factor: fuel_factor = 1 + (fuel_surcharge ÷ 100)
  • Overage penalty (optional): penalty = max(0, km − max_distance) × penalty_per_km_over
  • Shipping per order: ship = (km × cost_per_km + penalty) × fuel_factor × peak_multiplier
  • Variable cost per order: var = handling_cost + ship
  • Variable total: var_total = Σ(var × assigned_orders × planning_days)
  • Fixed total: fixed_total = Σ(fixed_cost × planning_days) for used warehouses
  • Grand total: grand_total = var_total + fixed_total
  • Average cost per order: avg = grand_total ÷ (orders_per_day × planning_days)

Note: This is a practical heuristic for quick planning. For strict global optimization, a linear programming solver is typically used.

How to use this calculator

  1. Set currency, planning days, shipping cost per km, and surcharges.
  2. Enter each warehouse name, daily capacity, fixed daily cost, and handling cost per order.
  3. Enter each region name and daily demand in orders.
  4. Fill the distance matrix in kilometers for each warehouse-to-region lane.
  5. Click Calculate Plan to view allocation and utilization above.
  6. Use Download CSV or Download PDF to export results.

Demand Forecasting and Service Targets

Daily demand by region is the backbone of distribution planning. Convert monthly order history into an average orders‑per‑day baseline, then apply growth, seasonality, and promotion uplift. Service targets translate into practical limits: a max delivery radius, a preferred lane distance, and an acceptable share of split shipments. When demand is uncertain, plan with a conservative peak multiplier so capacity and transport budgets remain resilient.

Capacity and Throughput Constraints

Warehouse capacity should reflect real throughput, not just storage. Start with pick‑pack lines, labor hours, carrier cutoff times, and average minutes per order. Translate these into a daily capacity figure and validate it against recent performance. A good plan keeps utilization high without creating bottlenecks, typically leaving headroom for returns processing, rework, and late inbound receipts. If unmet demand appears, it signals a need for overtime, temporary labor, or an additional node.

Cost Structure and Lane Economics

Total fulfillment cost combines fixed and variable components. Fixed cost includes rent, core staffing, and systems overhead per day. Variable cost includes handling per order and distance‑based shipping. Lane economics improve when you reduce long‑distance shipments and allocate orders to the lowest variable cost option that still has capacity. Penalizing distances above a policy threshold helps enforce service commitments and discourage inefficient lanes in practice.

Inventory Placement and Risk Buffers

Distribution decisions should align with inventory availability. Regions with volatile demand benefit from safety stock positioned closer to customers, while stable regions can be served from fewer nodes. Keep a buffer for carrier disruptions and weather events by spreading critical volume across at least two warehouses when possible. Review single‑point dependencies, including one warehouse supplying the highest revenue region, and define a contingency routing plan.

Operational Review and Continuous Improvement

After running scenarios, compare the recommended allocation against actual shipment data. Track average cost per order, miles per order, utilization, and unmet demand. Investigate costly lanes and test changes such as renegotiated carrier rates, packaging improvements, or a new cross‑dock strategy. Recompute the plan weekly during steady periods and daily during peak. Small adjustments to costs, capacities, and distances often produce meaningful savings.

FAQs

1) What does this planner optimize?

It assigns each region’s daily demand to available warehouses by the lowest variable cost per order while respecting capacity. Fixed costs are added only for warehouses that ship orders during the planning window.

2) How should I estimate warehouse capacity?

Use recent throughput: orders processed per hour × staffed hours, adjusted for carrier cutoff times and expected returns workload. Treat capacity as a realistic daily maximum, not a best‑case peak.

3) What distance value should I enter?

Use typical driving distance or an average carrier zone estimate between each warehouse and region. Consistent inputs matter more than perfect precision, especially when you compare scenarios over time.

4) Why is there unmet demand?

Unmet demand appears when total regional demand exceeds total warehouse capacity, or when you leave warehouses blank. Increase capacity, add another node, or reduce peak multiplier to test alternatives.

5) How do fuel surcharge and peak multiplier work?

Fuel surcharge increases distance‑based shipping cost as a percentage. Peak multiplier scales that shipping cost again to reflect congestion, surge pricing, or seasonal rate inflation.

6) Can I enforce a service radius?

Yes. Set a max distance and a penalty per kilometer over that limit. The penalty pushes allocation toward nearer warehouses, making long lanes less attractive when capacity allows.

Warehouse Distribution Planner • Designed for quick scenario planning.

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Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.