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GOFIBER Linear Program Solver
x402
GOFIBER Linear Program Solver is a paid API for AI agents from gofiber.hr, paid per call via x402, $0.05/call, status unknown (last checked 2026-10-22).
Solves linear programming (LP) and mixed-integer programming (MIP) optimization problems, returning the optimal variable values and objective value.
Price / call$0.05
Success—
StatusUnknown
How this service works
GOFIBER d.o.o. iz Petrinje izvodi elektroinstalacije, strukturno mrežno kabliranje, videonadzor i WAGO PLC automatizaciju u Sisačko-moslavačkoj županiji i šire. Brza ponuda.
Output
Returns a job result containing: optimal variable values array (x), objective value, solver status (e.g. OPTIMAL), number of variables, optimization sense, execution time in milliseconds, a verification report from an independent solver (scipy HiGHS), input and result SHA-256 hashes, tool version metadata, and constraint violation checks. The result is independently verified for correctness.
Example use cases
Production mix optimization
“I need to maximize profit for my factory. Each unit of product A earns $3 and product B earns $2. I have constraints: total units can't exceed 4, and A + 3×B can't exceed 6. Both quantities must be non-negative. What's the optimal production mix?”
Cost minimization with resource limits
“Help me minimize costs: my cost function is 5x + 4y. I need x + y ≥ 10 and 2x + y ≥ 14, with x and y both ≥ 0. What values of x and y minimize total cost?”
Integer resource allocation
“I need to allocate whole units of two resources to maximize output of 7x + 5y, with constraints 2x + y ≤ 20 and x + 2y ≤ 16, both variables must be non-negative integers. What's the optimal allocation?”
Technical details
Endpoint
POSThttps://gofiber.hr/x402/math/linear-program?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to solve continuous linear programs or mixed-integer linear programs with up to 500 variables and 500 constraints, and want an independently verified result with full audit trail (SHA-256 hashes, solver metadata). Useful for production optimization, resource allocation, scheduling, and any scenario requiring a provably correct LP/MIP solution via a pay-per-use micropayment API.
Side effects
- Infeasible problem: constraints contradict each other, solver returns INFEASIBLE status
- Unbounded problem: objective can grow without limit, returns UNBOUNDED status
- Dimension mismatch: coefficients array length doesn't match number of variables
- Too many variables or constraints: exceeds 500-item limits
- Invalid constraint operator: only <=, >=, == are supported
- Malformed bounds array: bounds must be pairs of [lower, upper] or null for unbounded
- Payment failure: x402 micropayment of $0.05 USDC not completed
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| sense | string | |
| bounds | — | |
| objective | array | |
| constraints | array | |
| integrality | — |
Output
Schema · Response
{
"type": "json",
"example": {
"job_id": "3f2a9c8e7b6d5a4f3e2d1c0b9a8f7e6d5c4b3a2f1e0d9c8b7a6f5e4d3c2b1a09",
"result": {
"tool": "linear_optimizer",
"result": {
"x": [
4,
0
],
"kind": "LP",
"status": "OPTIMAL",
"objective": 12,
"variables": 2,
"objective_sense": "maximize"
},
"status": "ok",
"rendered": null,
"verified": true,
"warnings": [],
"request_id": "27c18c6b0a714152b16575b4e3c85b43",
"execution_ms": 24.925,
"input_sha256": "106821473b3096dbb61e159249da4fe206f158e8290552008d21136b646eaf30",
"tool_version": {
"tool": "linear_optimizer",
"digest": "386013b1aa45ec65149534a3818dd74799a673216db34a43293aa4ee6880116b",
"params": {
"kind": "LP",
"sense": "maximize",
"tolerance": 0.000001,
"variables": 2,
"node_limit": 10000,
"constraints": 2,
"max_iterations": 2000,
"integrality_tolerance": 0.000001
},
"environment": {
"blas": "scipy-openblas",
"python": "3.12.13",
"system": "Linux",
"machine": "x86_64",
"libraries": {
"numpy": "2.2.1",
"scipy": "1.15.0",
"sympy": "1.14.0",
"ortools": "9.11.4210",
"networkx": "3.4.2"
},
"blas_version": "0.3.28",
"implementation": "CPython"
},
"tool_impl_version": "1.0.0"
},
"verification": {
"solver": "scipy.linprog/highs",
"message": "Optimization terminated successfully. (HiGHS Status 7: Optimal)",
"tolerance": 0.000001,
"comparison": "numerical_equivalence",
"iterations": 2,
"claim_scope": "independent_feasibility_and_objective_check",
"bounds_valid": true,
"constraint_count": 2,
"integrality_valid": true,
"solver_status_code": 0,
"max_bounds_violation": 0,
"objective_recomputed": -12,
"integrality_tolerance": 0.000001,
"max_integrality_error": 0,
"objective_discrepancy": 0,
"max_constraint_violation": 0
},
"result_sha256": "d52eccf35cd9e4ed60b4ed8a1da0a08421c5bb612118b5a63d203c31a85591e8",
"schema_version": 1,
"non_finite_fields": [],
"non_finite_detected": false
},
"status": "FULFILLED",
"result_url": "https://gofiber.hr/x402/jobs/3f2a9c8e7b6d5a4f3e2d1c0b9a8f7e6d5c4b3a2f1e0d9c8b7a6f5e4d3c2b1a09/result",
"status_url": "https://gofiber.hr/x402/jobs/3f2a9c8e7b6d5a4f3e2d1c0b9a8f7e6d5c4b3a2f1e0d9c8b7a6f5e4d3c2b1a09"
}
}Tags
x402
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