# Gyorgy Matyasfalvi (9 notebooks)¶

## Capacity expansion of power generation¶

Description: Models the extensive form of a deterministic multi-stage capacity expansion problem. In this model we can have multiple resources of the same type which have identical properties. The model can be further developed into a stochastic one.

## Introduction to Linear and Integer Programming¶

Description: Basic introduction to linear programming and AMPL via a lemonade stand example

## Introduction to Mathematical Optimization¶

Description: Basic introduction to optimization and AMPL via unconstrained optimization

## Network Linear Programs¶

Description: Basic introduction to network linear programms and AMPL via max flow and shortest path problems

## Plot feasible region¶

Description: Plot the feasible region and optimal solution for a simple two variable model using AMPL’s Python API.

## Pricing and target-market¶

Description: Formulate a pricing optimization and target-market problem as a MILP.

## Production Model¶

Description: Basic introduction to AMPL’s indexed entities and the Pygwalker Python package via a lemonade stand example

## Stochastic Capacitated Facility Location Problem¶

Description: This notebook illustrates modeling a stochastic facility location problem using a mixed-integer programming approach. Facility location decisions are pivotal, typically requiring substantial investments that have far-reaching social, economic, and environmental consequences.

## Unit Commitment for Electrical Power Generation¶

Description: This notebook illustrates the power generation problem using AMPL. The original version featured the Gurobi solver. By default, this notebook uses the HiGHS and CBC solvers.