Project 1

Project 1#

Summary: With a partner, you will explore an optimization model/case study using Pyomo.

Learning Goals#

By completing this project, you will:

  • Practice formulating and analyzing optimization problems on paper

  • Develop proficiency in Python and Pyomo

  • Analyze and discuss optimization results

  • Make publication quality figures

Choosing a Problem#

Select an optimization problem of interest to your team. Recommendation: choose a simple optimization problem from literature or a textbook. You want to choose an optimization problem where all of the input data/parameters are available and a model has already been formulated. Recommended resources to find examples:

Your project must enhance or extend the source reference material. For example, if you reproduced an optimization example from a textbook, you should perform a small additional analysis to gain a new insight about the problem not already discussed in the reference. If you choose an example that already has a Pyomo implementation, you need to extend the model in some way; this ensures that everyone gets some Pyomo practice in the project.

Deliverable: Jupyter Notebook#

Prepare a Jupyter notebook similar to our class examples. Your notebook should include:

  • Problem definition

  • Description (and possible visualization) of the data sources

  • Optimization model typeset and explained

  • If appropriate, a diagram to explain the problem description or optimization problem

  • Degree of freedom analysis for the optimization problem

  • Optimization model implemented and solved in Pyomo

  • Analysis including at least one visualization of the optimization solution(s)

  • A short paragraph explaining how your paragraph goes beyond the reference material

  • A list of references, including all sources for data, models, figures, codes, etc.

You and your partner will contribute these notebooks to the class website.

Deliverable: Class Presentation#

You and your partner will give a 5-minute presentation to the class. Your presentation should:

  • Clearly state the problem and summarize the input data

  • Provide an overview of the optimization formulation. What type of optimization problem is it? How many variables and constraints?

  • Present and analyze the optimization results

  • Draw at least one conclusion from the optimization results

  • Your slides should be professionally formatted including:

    • Slide numbers

    • References for all sources for data, figures, models, codes, etc. you did not create

    • Publication quality figures

    • Font large enough to see from the back of our classroom on the projector

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