Notebooks#
- AMPL - solve multiple models in parallel
- AMPL - spreadsheet handling with amplxl
- AMPL Bin Packing Problem with GCG
- AMPL Capacitated p-Median Problem with GCG
- AMPL Christmas Model created by ChatGPT
- ChatGPT & AMPL
- Christmas model by ChatGPT
- Load data directly from python data structures using amplpy
- Solve with HiGHS and retrieve solution
- Change the budget and solve with Gurobi
- Change the budget once again and solve with CBC
- Some useful information:
- AMPL Development Tutorial 1/6 – Capacitated Facility Location Problem
- AMPL Development Tutorial 2/6 – Stochastic Capacitated Facility Location Problem
- AMPL Development Tutorial 3/6 – Benders Decomposition via AMPL scripting
- AMPL Development Tutorial 4/6 – Benders Decomposition via PYTHON scripting
- AMPL Development Tutorial 5/6 – Parallelizing Subproblem Solves in Benders Decomposition
- AMPL Development Tutorial 6/6 – Implementing Benders Decomposition with ampls
- AMPL Model Colaboratory Template
- Solve with HiGHS
- Retrieve solution as a pandas dataframe
- Aircrew trainee scheduling with seniority constraints
- Book Example: Economic equilibria
- Book Example: Transshipment problem
- Book Example: diet
- Book Example: prod
- Book Example: steel
- Book Example: transp
- CP-style scheduling model with the numberof operator, solved by a MIP solver
- Capacity expansion of power generation
- Containers scheduling
- Containers scheduling
- Model
- Debugging Model Infeasibility
- Diet lecture
- Diet model with Google Sheets
- Autheticate in order to use Google Sheets
- Use
%%ampl_eval
to evaluate AMPL commands - Define the model
- Instatiate gspread client
- Open speedsheet using name or URL
- Define auxiliar functions to convert data from worksheets into dataframes
- Load data from the first worksheet
- Load the data from the second worksheet
- Load the data from the third worksheet
- Use
%%ampl_eval
to solve the model with cbc - Retrieve the solution as a pandas dataframe
- Dual-Donor Organ Exchange problem
- Dynamic routing example
- AMPL solution method
- “Glue” functions
- Efficient Frontier with Google Sheets
- Install needed modules and authenticate user to use google sheets
- Auxiliar functions
- Efficient Frontier Example
- Employee Scheduling Optimization
- Financial Portfolio Optimization with amplpy
- Downloading data and callculate
mu
andS
- Minimize volatility
- Maximize return for a target risk
- Minimizing volatility for a given target return
- Maximize the Sharpe Ratio
- Maximize quadratic utility
- Maximize return for a target risk with sector constraints
- Maximize return for a target risk with cardinality constraints
- Downloading data and callculate
- Google Hashcode 2022
- First formulation
- Alternative formulation
- Conclusion
- Hospitals-Residents MIP
- Hydrothermal Scheduling Problem with Conic Programming
- Introduction to Linear and Integer Programming
- EXERCISE 5
- SOLUTION
- EXERCISE 6
- SOLUTION
- EXERCISE 7
- SOLUTION
- Introduction to Mathematical Optimization
- EXERCISE 1
- EXERCISE 2
- EXERCISE 3
- EXERCISE 4
- Jupyter Notebook Integration
- Labs scheduling
- The problem
- Data
- Model
- Solving
- Solution
- Largest small polygon
- Logistic Regression with amplpy
- Modeling in AMPL
- 1. Initial example with a small data set
- 2. A larger data set
- Discussion
- Magic sequences
- Description
- Constraint Programming formulation
- Better models
- Exercices
- Multicommodity transportation problem
- N-Queens
- NFL Team Rating
- Network Linear Programs
- Maximum Flow Models
- NETWORK EXERCISE
- SOLUTION
- Concluding Remarks
- Network design with redundancy
- Network
- Nonlinear transportation model
- Nonlinear transportation problem example
- Oil refinery production optimization
- Oil refinery production optimization (+PowerBI)
- 1. Introduction
- 1. Download Necessary Extensions and Libraries
- 2. Authorize in Power BI Service
- 3. Embed the Power BI Report with Data
- 4. AMPL Model Formulation
- 5. Data change
- 5. Download Data from Power BI Report
- 6. Load Data into AMPL
- 7. Solve the Problem
- 6. Display the solution
- 7. Retrieve solution and export it to a *.xlsx file
- 8. Retrieve solution and export it to a Google Sheets document
- Load Data into the Power BI Report from Google Sheets
- Oil refinery production optimization (ampl-only version)
- Optimal Power Flow with AMPL and Python - Bus Injection Model (BIM)
- Optimal Power Flow with AMPL and Python - Bus Injection Model (BIM) with controllable-phase shifting transformers and tap-changing transformers
- Optimal Power Flow with AMPL and Python - DC Power Flow
- Optimal Power Flow with AMPL and Python - conventional Power Flow
- Optimal Power Flow with AMPL and Python - data management
- Optimization Methods in Finance: Chapter 3
- Bond dedication
- Optimization of Reinforced Concrete Production and Shipment: A Conveyor-Based Manufacturing and Curing Model
- Optimization of an TV advertising campaign based on TRP, GRP indicators
- Optimization of an advertising campaign for launching a new product on the market
- Optimize your Christmas Tree to Global Optimality
- 🎅 Global Non-Linear Optimization
- Optimize your Christmas 🎄 to Global Optimality!
- Optimizing the number of staff in a chain of stores
- 1. Introduction
- 2. Pharmacy Network Overview
- P-Median problem
- Pattern Enumeration
- Pattern Generation
- Plot feasible region
- Pricing and target-market
- Production model
- Production model
- Profit Maximization for Developers: Optimizing Pricing, Marketing, and Investment Strategies
- Project management: Minimizing the cost of implementing an investment project, taking into account the costs and risks of completing tasks and penalties for late fulfillment of obligations.
- Quick Start using Pandas dataframes
- Diet Model
- Solve with HiGHS
- Quick Start using lists and dictionaries
- Diet Model
- Solve with HiGHS
- Robust Linear Programming with Ellipsoidal Uncertainty
- Diet problem with uncertain costs
- Roll Cutting - Revision 1 & 2
- Scheduling Multipurpose Batch Processes using State-Task Networks in Python
- Simple sudoku solver using logical constraints (with GUI)
- Solution check: discontinuous objective function
- Solving a nonogram puzzle
- Solving simple stochastic optimization problems with AMPL
- Manual solution
- Maximize expected returns
- Maximize worst case
- Maximize worst alpha percentile (\(\alpha\)-Value at Risk)
- Minimize Conditional Value at Risk (\(CVaR_\alpha\))
- Mixture of CVaR and Expected value
- Comparing solution approaches and behavior
- Steel industry problem
- Sudoku Generator
- Supply chain network
- Transportation problem
- Travelling Salesman Problem with subtour elimination
- Unit Commitment for Electrical Power Generation
- VPSolver: Cutting & Packing Problems
- Warehouse location and transport
- Problem
- Formulation
- amplpy setup & Quick Start