Random Warehouse Order Fulfillment Dataset Generator

Description

Construct synthetic orders with actual ordered/shipped line quantities and independent on-time draws, then delegate complete-line fill, backorder and delivered-order OTIF metrics. A delivery means any positive shipment; OTIF requires every line complete and on time, zero shipments are not delivered, and no delivered orders yields an explicit undefined OTIF rather than zero.

A logistics test dataset combines supplied operating ranges with explicit quantity and unit conventions. Constructed measurements and calculated indicators can exercise reports and calculators without claiming to represent an observed operation or a safe physical plan.

When to use this tool

Use this generator to create reproducible warehouse order fulfillment dataset cases from the supplied model or bank. Inspect the returned evidence before using cases in a test or exercise.

How to use the tool and how it works

Supply orderCount, minimumLines, maximumLines, minimumUnits, maximumUnits, onTimeProbability in the field shapes below. Set seed when you need an explicit replay.
Run the tool and correct any input error. For generated controls, distinguish a successful fixture containing an invalid case from failure to generate the fixture.
Read orders, totals, metrics. Use the conventions below and keep answer-bearing fields separate when presenting an exercise.

Draw order lines and quantities, sample shipped units from zero through ordered units and draw on-time status for positive shipments. Mark any-positive-shipment orders as delivered and require every line complete and timely for OTIF. Delegate line-fill/backorder percentages and delivered-order OTIF.^[1]

Delegated operations used for this result: fill rate line item percent; backorder rate percent. Their calculation or parsing conventions apply to the corresponding result fields.^{[2, 3]}

Input field	Meaning and units	Accepted input
orderCount	Order Count	Required. Safe integer; minimum 1; maximum 128.
minimumLines	Minimum Lines	Required. Safe integer; minimum 1; maximum 16.
maximumLines	Maximum Lines	Required. Safe integer; minimum 1; maximum 16.
minimumUnits	Minimum Units	Required. Safe integer; minimum 1; maximum 9007199254740991.
maximumUnits	Maximum Units	Required. Safe integer; minimum 1; maximum 9007199254740991.
onTimeProbability	On Time Probability	Required. Finite number; minimum 0; maximum 1.
seed	Optional numeric seed; takes precedence over context randomness. Without either, use the fixed tool.io default seed.	Optional. Safe integer.

Output field	Interpretation	Returned shape
orders	Orders	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 128.
orders[].id	Literal identifier used to match records, independently of their display labels.	Required. Text.
orders[].lines	Lines	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 16.
orders[].lines[].orderedUnits	Ordered Units	Required. Safe integer; minimum 1; maximum 9007199254740991.
orders[].lines[].shippedUnits	Shipped Units	Required. Safe integer; minimum 0; maximum 9007199254740991.
orders[].lines[].onTime	On Time	Required. Boolean.
orders[].delivered	Delivered	Required. Boolean.
orders[].inFull	In Full	Required. Boolean.
orders[].onTimeInFull	On Time In Full	Required. Boolean.
totals	Totals	Required. Object; no unknown keys.
totals.lineItemsOrdered	Line Items Ordered	Required. Safe integer; minimum 1; maximum 9007199254740991.
totals.lineItemsShippedInFull	Line Items Shipped In Full	Required. Safe integer; minimum 0; maximum 9007199254740991.
totals.lineItemsBackordered	Line Items Backordered	Required. Safe integer; minimum 0; maximum 9007199254740991.
totals.unitsOrdered	Units Ordered	Required. Safe integer; minimum 1; maximum 9007199254740991.
totals.unitsShipped	Units Shipped	Required. Safe integer; minimum 0; maximum 9007199254740991.
totals.ordersDelivered	Orders Delivered	Required. Safe integer; minimum 0; maximum 9007199254740991.
totals.ordersOnTimeInFull	Orders On Time In Full	Required. Safe integer; minimum 0; maximum 9007199254740991.
metrics	Metrics	Required. Object; no unknown keys.
metrics.fillRatePercent	Fill Rate Percent	Required. Finite number; minimum 0; maximum 100.
metrics.backorderRatePercent	Backorder Rate Percent	Required. Finite number; minimum 0; maximum 100.
metrics.otifPercent	Otif Percent	Required. Finite number; minimum 0; maximum 100. or Null.
metrics.otifUndefinedReason	Otif Undefined Reason	Required. Text; exactly "no-delivered-orders". or Null.
randomness	Replay metadata: source is seed or context; seed is the normalized 32-bit seed or null for a context source.	Required. Object; no unknown keys.
randomness.seed	Optional numeric replay seed; normalization and precedence are explained below.	Required. Safe integer. or Null.
randomness.source	Source	Required. Text; one of "context", "seed".

An explicit safe-integer seed takes precedence over injected context randomness and is normalized to an unsigned 32-bit integer. With no seed and no context source, replay uses the fixed tool.io default seed. A context source must return finite values from zero inclusive to one exclusive; its advancing state must be retained separately. randomness records the source and normalized seed, or null for context. These generators are not cryptographic random sources.

json

{
  "input": {
    "orderCount": 3,
    "minimumLines": 1,
    "maximumLines": 3,
    "minimumUnits": 1,
    "maximumUnits": 5,
    "onTimeProbability": 0.7,
    "seed": 42
  },
  "output": {
    "orders": [
      {
        "id": "order-1",
        "lines": [
          {
            "orderedUnits": 3,
            "shippedUnits": 3,
            "onTime": true
          },
          {
            "orderedUnits": 1,
            "shippedUnits": 1,
            "onTime": true
          }
        ],
        "delivered": true,
        "inFull": true,
        "onTimeInFull": true
      },
      {
        "id": "order-2",
        "lines": [
          {
            "orderedUnits": 5,
            "shippedUnits": 2,
            "onTime": true
          },
          {
            "orderedUnits": 5,
            "shippedUnits": 4,
            "onTime": true
          }
        ],
        "delivered": true,
        "inFull": false,
        "onTimeInFull": false
      },
      {
        "id": "order-3",
        "lines": [
          {
            "orderedUnits": 3,
            "shippedUnits": 2,
            "onTime": true
          }
        ],
        "delivered": true,
        "inFull": false,
        "onTimeInFull": false
      }
    ],
    "totals": {
      "lineItemsOrdered": 5,
      "lineItemsShippedInFull": 2,
      "lineItemsBackordered": 3,
      "unitsOrdered": 17,
      "unitsShipped": 12,
      "ordersDelivered": 3,
      "ordersOnTimeInFull": 1
    },
    "metrics": {
      "fillRatePercent": 40,
      "backorderRatePercent": 60,
      "otifPercent": 33.33333333333333,
      "otifUndefinedReason": null
    },
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

No delivered orders yields null OTIF with an explicit reason. Line metrics and unit totals have different denominators; independent synthetic draws do not reproduce real fulfillment or customer-service performance.
A replay requires the same complete input and implementation. Randomized construction does not guarantee uniform coverage of every feasible output; finite samples can repeat unless a distinct-selection rule is explicitly stated.
The field tables state structural bounds; cross-field constraints and bounded search or output budgets also apply. Unknown keys are rejected where the object contract disallows them. Input errors are distinct from null fields and deliberate invalid controls in a successful output.

Alternative or Complementary methods

For a supplied example, inspect the returned construction or delegated check directly. To evaluate a consumer, also test cases chosen for its own boundaries; a generated finite corpus does not establish exhaustive coverage.

References

Tool behavior and example: Random Warehouse Order Fulfillment Dataset Generator — tool.io
Calculation or validation: logistics/fill-rate-line-item-percent — tool.io
Calculation or validation: logistics/backorder-rate-percent — tool.io

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