Description
Generate a single-depot Euclidean capacitated routing instance for identical vehicles with positive integer demands and a planted round-robin feasible route set; dimension/bound combinations must guarantee capacity, with no optimality or real-road claim.
An optimization instance defines choices, constraints, and an objective. A feasible witness demonstrates that its stated constraints can be met; it establishes optimality only when the tool actually computes and verifies an optimum.
Generate a single-depot Euclidean capacitated routing instance for identical vehicles with positive integer demands and a planted round-robin feasible route set; dimension/bound combinations must guarantee capacity, with no optimality or real-road claim.
When to use this tool
Use this generator to create reproducible vehicle routing instance 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 customerCount, vehicleCount, vehicleCapacity, minimumDemand, maximumDemand, minimumCoordinate, maximumCoordinate 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 points, distances, demands, vehicleCapacity, routes, routeLoads, routeLengths, totalLength. Use the conventions below and keep answer-bearing fields separate when presenting an exercise.
Draw integer-coordinate depot/customers and a complete Euclidean distance matrix. Draw positive demands and assign a shuffled customer order round-robin to identical vehicles, adding depot zero at both ends. Return route loads, measured lengths and total length.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| customerCount | Customer Count | Required. Safe integer; minimum 1; maximum 63. |
| vehicleCount | Vehicle Count | Required. Safe integer; minimum 1; maximum 32. |
| vehicleCapacity | Vehicle Capacity | Required. Safe integer; minimum 1; maximum 9007199254740991. |
| minimumDemand | Minimum Demand | Required. Safe integer; minimum 1; maximum 9007199254740991. |
| maximumDemand | Maximum Demand | Required. Safe integer; minimum 1; maximum 9007199254740991. |
| minimumCoordinate | Minimum Coordinate | Required. Safe integer. |
| maximumCoordinate | Maximum Coordinate | Required. Safe integer. |
| 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 |
|---|---|---|
| points | Points | Required. Array of Array of Safe integer.; minimum items 2; maximum items 2.; minimum items 2; maximum items 64. |
| distances | Distances | Required. Array of Array of Finite number; minimum 0.; minimum items 2; maximum items 64.; minimum items 2; maximum items 64. |
| demands | Demands | Required. Array of Safe integer; minimum 0; maximum 9007199254740991.; minimum items 2; maximum items 64. |
| vehicleCapacity | Vehicle Capacity | Required. Safe integer; minimum 1; maximum 9007199254740991. |
| routes | Routes | Required. Array of Array of Safe integer; minimum 0; maximum 63.; minimum items 2; maximum items 65.; minimum items 1; maximum items 32. |
| routeLoads | Route Loads | Required. Array of Safe integer; minimum 0; maximum 9007199254740991.; minimum items 1; maximum items 32. |
| routeLengths | Route Lengths | Required. Array of Finite number; minimum 0.; minimum items 1; maximum items 32. |
| totalLength | Total Length | Required. Finite number; minimum 0. |
| 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.
{
"input": {
"customerCount": 5,
"vehicleCount": 2,
"vehicleCapacity": 9,
"minimumDemand": 1,
"maximumDemand": 3,
"minimumCoordinate": 0,
"maximumCoordinate": 10,
"seed": 42
},
"output": {
"points": [
[
6,
4
],
[
9,
7
],
[
1,
5
],
[
3,
6
],
[
9,
5
],
[
2,
9
]
],
"distances": [
[
0,
4.242640687119286,
5.099019513592785,
3.6055512754639896,
3.1622776601683795,
6.4031242374328485
],
[
4.242640687119286,
0,
8.246211251235321,
6.0827625302982185,
2,
7.280109889280519
],
[
5.099019513592785,
8.246211251235321,
0,
2.23606797749979,
8,
4.123105625617661
],
[
3.6055512754639896,
6.0827625302982185,
2.23606797749979,
0,
6.0827625302982185,
3.1622776601683795
],
[
3.1622776601683795,
2,
8,
6.0827625302982185,
0,
8.06225774829855
],
[
6.4031242374328485,
7.280109889280519,
4.123105625617661,
3.1622776601683795,
8.06225774829855,
0
]
],
"demands": [
0,
3,
1,
1,
2,
3
],
"vehicleCapacity": 9,
"routes": [
[
0,
5,
2,
4,
0
],
[
0,
3,
1,
0
]
],
"routeLoads": [
6,
4
],
"routeLengths": [
21.688507523218888,
13.930954492881494
],
"totalLength": 35.619462016100385,
"randomness": {
"seed": 42,
"source": "seed"
}
}
} Limitations and assumptions
- Capacity must cover ceil(customerCount/vehicleCount)×maximumDemand so the planted routes are feasible. Routes need not be optimal, coordinates may coincide, and Euclidean geometry is not a real-road or travel-time model.
- 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
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