Course Resources
This page contains various resources to support your learning in the Analytics Project course. The resources are organized into categories for easy navigation.
1. Theory & Concepts
- Algorithms for Optimization - Free online textbook by M. J. Kochenderfer and T. A. Wheeler
- Algorithms for Decision Making - Free online textbook by M. J. Kochenderfer, T. A. Wheeler, and K. H. Wray
- Engineering Design Optimization - Free textbook by J. Martins and A. Ning
- Prescriptive Analytics Project Book - Course book draft
2. Lectures
2.1 Slides
2.2 Recordings
- Available in MyITS Classroom (requires login)
3. Assignments & Guidelines
- Project Proposal Guidelines
- Peer Review Guidelines
- Midterm Report Guidelines
- Final Report Guidelines
- Final Presentation Guidelines
- AI Usage and Reflection Form
4. Model Examples
4.1 Optimization Models
-
Mixed integer linear optimization with Pyomo and GLPK
-
Mixed integer linear programming with Pyomo and Gurobi
-
Surrogate objective optimization with ZOOpt
-
Simple 1D nonlinear optimization with Pyomo and Ipopt
-
Simple 2D nonlinear optimization with Pyomo and Ipopt
-
Nonlinear optimization with ZOOpt
4.2 Tutorials
Tutorials are great way to get hands-on experience with the concepts and tools we’ll be using in the course.
-
Optimization Modeling
- Sets Definition
- Decision Variables Definition
- Parameter Definition
- Expressions Definition
- Objective Function Definition
- Constraints Definition
- Sets Definition
- Verification & Validation
- Prototyping
- Building a demo in Gradio
- Building a demo in Gradio
5. Past Projects
- Project Template
- 2024 Gasal Project Galleries
- 2024 Genap Project Gallery
- Demos
- Polytama-ITS Demo🔒 (access restricted)
- PPC Demo with Gradio
- PPC Demo with Streamlit
- Stock Portfolio Demo with Streamlit
6. Open-source Modeling Tools
6.1 Python Packages
- Pyomo - Optimization modeling language
- PuLP - Linear programming toolkit
- CVXPY - Convex optimization
- OR-Tools - Google’s optimization suite
- PyTorch - Machine learning framework
6.2 Julia Packages
- JuMP.jl - Mathematical optimization in Julia
- Optim.jl - Optimization package
- Flux.jl - Machine learning library
- POMDPs.jl - POMDP and MDP tools
7. Solvers
- GLPK - Linear programming solver
- Gurobi - Optimization solver
- Ipopt - Nonlinear programming solver
- CPLEX - Optimization solver
- Bonmin - Nonlinear programming solver
- Couenne - Nonlinear programming solver