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mixed-integer-optimization

// Mixed-integer linear and nonlinear programming

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updated:March 4, 2026
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SKILL.md Frontmatter
namemixed-integer-optimization
descriptionMixed-integer linear and nonlinear programming
allowed-toolsBash,Read,Write,Edit,Glob,Grep
metadata[object Object]

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