cuopt-numerical-optimization-formulation

Installation
SKILL.md

Numerical Optimization Formulation

Concepts and workflow for going from a problem description to a clear formulation across LP, MILP, and QP. No API code here.

What is LP / MILP / QP

  • LP: Linear objective, linear constraints, continuous variables.
  • MILP: Same as LP plus some integer or binary variables (e.g., scheduling, facility location, selection).
  • QP: Quadratic objective (e.g., x², x·y terms — portfolio variance, least squares), linear constraints. QP support in cuOpt is currently in beta.

Identifying problem type

Property LP MILP QP
Objective Linear Linear Quadratic (xᵀQx + cᵀx)
Constraints Linear Linear Linear (no quadratic constraints)
Variables Continuous Mixed: continuous + integer/binary Continuous
Sense min or max min or max minimize only (negate to max)
Installs
159
Repository
nvidia/skills
GitHub Stars
1.0K
First Seen
7 days ago
cuopt-numerical-optimization-formulation — nvidia/skills