Examples of using the Python interface
- Using NumPy arrays to create variables
- Visualize the BB tree
- Irreducible Infeasible Sets
- Loading a problem
- Using Python model objects to build a problem
- Changing the optimization problem
- Extending a problem
- Using NumPy and Xpress
- Finding an LP subsystem with as many constraints as possible
- Basis and Stability
- Solving a quadratically constrained problem
- Solving a nonconvex quadratic problem
- Solving a quadratically problem
- Repeatedly solving a problem
- Using indicators
- Using special ordered sets
- The travelling salesman problem
- Solving a TSP using NumPy
- Writing and reading problem files
- The feasiblity pump
- Knapsack problem
- The n-queens problem
- Min-cost-flow problem
- Solving Sudoku
- Comparing Matrices
- Multicommodity flow problem
- Find largest-area inscribed polygon
- Read problem data into matrix and vectors
- Solve a nonconvex MIQCQP problem
- Solve a simple MIP using Benders decomposition
- Create a problem with piecewise linear functions
- Use the API to create a model with piecewise linear functions
- Create a problem with general constraints that use operator abs
- Create a problem with general constraints with the operator abs by using the API
- Create a problem with general constraints that use operator max
- Create a problem with general constraints with operator max by using the API
- Create a problem with logical constraints
- Create a problem with general constraints with logic operators by using the API
- Create an iterative algorithm cutting stock problem
- Maximize the sum of logistic curves subject to linear and piecewise linear constraints
- Transportation problem with piecewise-linear costs
- Modeling Satisfiability (SAT) problems with MIP
- Modeling PseudoBoolean Optimization problems with MIP
- Re-solving problem using the Barrier method's warm start
- Using the tuner functions in the Python interface
- Multi-objective knapsack problem
- Goal programming
- Markowitz portfolio optimization
- Basic LP tasks: problem statement and solving; solution analysis
- Network problem: transport from depots to customers
- Blend: A model for mineral blending
- Basic MIP tasks: binary variables; logic constraints
- Coco: The Coco productional planning problem
- Catenary: Determine chain shape
- Pplan: A project planning problem
- Firestns: A set-covering model for emergency service provision
- Solving a quadratically constrained problem
- Solve a polynomial optimization problem
- Modeling with user functions
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