The knapsack app is available in three modeling languages as a Mixed Integer Problem (MIP). You can also choose to make customizations to the model by instantiating the app first.
- OR-Tools
- Default solver:
SCIP - Marketplace subscription app IDs
- Python:
nextmv-knapsack.ortools - Java:
nextmv-knapsack.jortools
- Python:
- Default solver:
- Pyomo
- Default solver:
CBC - Marketplace subscription app IDs
- Python:
nextmv-knapsack.pyomo
- Python:
- Default solver:
- Nextmv SDK
- Default solver:
HiGHS - Marketplace subscription app IDs
- Go:
nextmv-knapsack.gosdk
- Go:
- Default solver:
Once you have the code locally, you can customize the model, run it locally and deploy it to Nextmv Platform.
Input
The input schema is a JSON payload defining the available items and the weight capacity of the knapsack for the knapsack problem. Nextmv's tools are designed to operate directly on business data (in JSON) to produce decisions that are actionable by software systems. This makes decisions more interpretable and easier to test. It also makes integration with data warehouses and business intelligence platforms significantly easier. An input contains the following components:
| Field name | Required | Data type | SI Unit | Description | Example |
|---|---|---|---|---|---|
items | Yes | array of item | NA | Possible items to select into the knapsack. | See item |
weight_capacity | Yes | int | NA | The weight capacity of the knapsack. | {"weight_capacity": 50} |
Here you can find a sample .json with the input schema:
Item
An item is used in the input schema.
| Field name | Required | Data type | Description | Example |
|---|---|---|---|---|
id | Yes | string | ID for the item. | {"id": "cat"} |
value | Yes | int | The value of the item. | {"value": "100"} |
weight | Yes | int | The weight of the item. | {"weight": 20} |
Output
The output schema defines the solution to the knapsack problem in JSON format. The output schema contains the following components.
| Field name | Always present | Data type | SI Unit | Description | Example |
|---|---|---|---|---|---|
solutions | Yes | array of solution | NA | Solutions to the knapsack problem. | {"solutions": []} |
statistics | Yes | statistics | NA | Summary statistics of the solution. | {"statistics": {"total_cost": 123}} |
Solution
| Field name | Always present | Data type | SI Unit | Description | Example |
|---|---|---|---|---|---|
items | Yes | array of item selected into the knapsack | NA | Solution to the knapsack problem. | {"items": []} |
Statistics
| Field name | Always present | Data type | SI Unit | Description | Example |
|---|---|---|---|---|---|
result | No | result | NA | Final result of the solutions. | See result |
run | Yes | run | NA | Information about the run. | See run |
schema | Yes | string | NA | Schema of the statistics. | {"schema": "v1"} |
Here you can find additional definitions used in the statistics schema:
resultField name Always present Data type SI Unit Description Example durationYes floatsecondsTime duration to get to the final result. {"duration": 0.123}valueYes floatNA Value of the final result. {"value": 0.123}customYes anyNA Custom solver metrics. See customrunField name Always present Data type SI Unit Description Example durationYes floatsecondsTime duration of the run. {"duration": 0.123}customField name Always present Data type SI Unit Description Example constraintsYes intNA Number of constraints. {"constraints": 123}providerYes stringNA Solver provider. {"provider": "highs"}statusYes stringNA Solver status. {"status": "optimal"}variablesYes intNA Number of variables. {"variables": 123}