Agent Skills

cuopt-numerical-optimization-api

LP, MILP, and QP (beta) with cuOpt — Python, C, and CLI. Use when the user is solving LP, MILP, or QP with any cuOpt interface.

Install

npx skills add https://github.com/nvidia/skills --skill cuopt-numerical-optimization-api
SKILL.md

cuOpt Numerical Optimization API

Model and solve LP, MILP, and QP problems using NVIDIA cuOpt's GPU-accelerated solver.

Interface Selection

Choose the reference for the user's interface:

Interface When to use Reference
Python User is writing Python code references/python_api.md
C / C++ User is embedding in a C/C++ application references/c_api.md
CLI User is solving from MPS files on the command line references/cli_api.md

If the interface is not yet clear, ask before writing any code.

Already using a modeling language? cuOpt also works as a solver backend for third-party modeling tools — AMPL, GAMS / GAMSPy, PuLP, JuMP, Pyomo, and CVXPY — with near-zero code changes (point the model's solver at cuOpt). CVXPY additionally covers convex QP and, in beta, QCQP / SOCP. Prefer this when the user already has a model in one of these tools rather than porting it to the cuOpt API. See Third-Party Modeling Languages.

Choosing LP vs MILP vs QP

Decide from the objective and variables:

If the objective is... And variables are... Use
Linear (sum of c_i * x_i) All continuous LP
Linear Some integer or binary MILP
Has squared (x*x) or cross (x*y) terms Continuous (integer QP not supported) QP (beta)

Prefer LP when the problem allows it. LP solves faster and has stronger optimality guarantees. Use MILP only when the problem logically requires whole numbers or yes/no decisions. Use QP only when the objective is genuinely quadratic (variance, squared error, kinetic energy).

  • Use LP when every quantity can meaningfully be fractional: flows, proportions, rates, dollars, hours, tonnes of material, etc.
  • Use MILP when the problem mentions counts of discrete entities, yes/no choices, or either/or decisions (e.g. open a facility or not, assign a person to a shift, number of trucks).
  • Use QP when the objective minimizes variance, squared error, or any expression with x*x or x*y terms (portfolio optimization, least squares, regularized regression).

Integer vs Continuous from Wording

Problem wording / concept Variable type Examples
Discrete entities (counts) INTEGER Workers, cars, trucks, machines, pilots, facilities, units to manufacture
Yes/no or on/off INTEGER (binary, lb=0 ub=1) Open a facility, run a machine, assign a person to a shift
Amounts that can be fractional CONTINUOUS Tonnes, litres, dollars, hours, kWh, proportion of capacity
Rates or fractions CONTINUOUS Utilization, percentage, share of budget

Rule of thumb: "How many things" → INTEGER. "How much" → CONTINUOUS.

QP Rules (all interfaces)

  • MINIMIZE only — the solver rejects MAXIMIZE for quadratic objectives. To maximize f(x), minimize -f(x) and negate the reported objective value.
  • Continuous variables only — integer QP is not supported.
  • Q should be positive semi-definite for a convex, well-posed problem.
  • Beta — API may evolve; treat as production-capable for typical convex QP.

Dual Values

Duals and reduced costs are available for LP and QP only:

  • MILP — no duals (integer optima are not continuous).
  • Quadratic constraints — duals unavailable even for LP/QP; all values return NaN.
  • PDLP warmstart — LP only; MILP solves do not accept a PDLP warmstart.

Common Issues (all interfaces)

Problem Likely cause Fix
Infeasible Conflicting constraints Check constraint logic and bounds
Unbounded Missing bounds Add variable bounds
Slow solve Large problem Set time limit; increase gap tolerance
QP rejected with MAXIMIZE QP only supports MINIMIZE Negate the objective; negate the result
QP returns non-optimal Q not PSD or badly scaled Check Q is PSD; rescale variables

Solver Settings (concepts)

Setting Purpose
time_limit Stop after N seconds
mip_relative_gap Stop MILP when within X% of optimal
mip_absolute_tolerance Absolute MIP gap stop
log_to_console Enable solver logging

Syntax varies by interface — see the interface reference file.

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