AI4Math-Optimization

Route AI4Math optimization tasks to the appropriate bundled skill package.

Models and solves linear programs (LP) with multiple solvers (COPT, Gurobi, MOSEK, CPLEX, HiGHS (scipy/highspy), CLARABEL, PuLP/CBC, CVXOPT, OR-Tools/GLOP, GLPK, SoPlex, lpsolve, ECOS). Restates natural-language word problems into LP before building and solving. When no local solver is available, searches GitHub for open-source LP solving code. Use when the user mentions linear programming, LP, word problems, applications, story problems, natural-language descriptions, 应用题, 线性规划文字题, matrix-form inequalities or equalities, and variable bounds.

Models and solves second-order cone programs and problems convertible to SOCP form using cvxpy with multiple solver backends (COPT, Gurobi, MOSEK, CPLEX, CLARABEL, ECOS, SCS, CVXOPT, COSMO, OSQP). Handles linear objectives with second-order cone constraints, as well as problems reducible to SOCP such as portfolio optimization, robust optimization, and engineering design. When no local solver is available, searches GitHub for open-source SOCP solving code.

Use when Codex needs to solve, reproduce, test, compare, generate examples for, or diagnose CDOpt manifold optimization workflows, including CDOpt package smoke tests, official problem description cards, Stiefel dictionary learning, SciPy wrappers, PyTorch/JAX/NumPy CDOpt examples, dependency checks, tiny CPU validation runs, comparison plans, or JSON result reporting.

Models and solves mixed-integer linear programs, including binary, integer, and continuous decision variables with linear objectives and constraints.

Unified solver detection, installation, selection, and license configuration for OR optimization skills (LP, MIP, SOCP). One-stop solver management: detect installed packages, install missing solvers with proper priority, select the best available solver by problem type, and troubleshoot common errors. Covers 20 solvers across commercial (COPT, Gurobi, MOSEK, CPLEX) and open-source (HiGHS, SCIP, CLARABEL, CBC, ECOS, SCS, etc.). Use when the LP, MIP, or SOCP skill needs to set up a solver environment, or when the user asks about solver installation, solver comparison, license setup, or solver selection.

Models and solves linear programs (LP) with Cardinal Optimizer (coptpy). Restates natural-language word problems into LP before building and solving. Use when the user mentions COPT/coptpy, linear programming, LP, word problems, applications, story problems, natural-language descriptions, 应用题, 线性规划文字题, or matrix-form constraints such as inequality systems, equality systems, and variable bounds.