Best use case
mixed-integer-optimization is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Mixed-integer linear and nonlinear programming
Teams using mixed-integer-optimization should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/mixed-integer-optimization/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How mixed-integer-optimization Compares
| Feature / Agent | mixed-integer-optimization | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Mixed-integer linear and nonlinear programming
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Mixed-Integer Optimization ## Purpose Provides capabilities for formulating and solving mixed-integer linear and nonlinear programming problems. ## Capabilities - Branch and bound/cut algorithms - MIP formulation techniques - Indicator constraints - Big-M reformulations - Lazy constraints - Solution pool generation ## Usage Guidelines 1. **Formulation**: Use tight formulations with valid inequalities 2. **Big-M Selection**: Choose appropriate Big-M values 3. **Branching**: Configure branching priorities 4. **Solution Pool**: Generate diverse feasible solutions ## Tools/Libraries - Gurobi - CPLEX - SCIP - CBC
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