- 22 December 2014 — Original version.

Your goal: write a report that

- describes the methodology you developed and used to solve your capstone project problem, and
- describes and interprets the results you have obtained.

This will eventually form the bulk of the final report you will submit at the end of the semester.

The best way to present your methodology and results will depend on the exact nature of your project. Your report should address the following in some shape or form.

Describe your problem mathematically.

- Define all the input parameters to your problem as symbols.
- Explain what constitutes a feasible solution to your problem: i.e. describe the constraints.
- Describe the objective of your problem.
- If you are modeling your problem as an optimization model (e.g., linear program, integer program, etc.), you can do the above by stating your model (input parameters, decision variables, objective function, constraint), along with a description in words.
- If you are designing your own algorithm to solve your problem, only define the input parameters that are necessary for your algorithm. Later, you can describe how you transform your raw data into the input parameters that you need.

For an example, take a look at the Sections 2 and 3 in the following article:

D. P. Morton, R. E. Rosenthal, L. T. Wang. Optimization modeling for airlift mobility.Military Operations Research1(4):49-67, 1996. [link]

Describe your methodology for solving your problem. Some or all of the following may apply.

- Describe how you collected and computed data for the problem (i.e. how did you come up with the numbers associated with all the input parameters you defined above?).
- Give an optimization model formulation (e.g. linear program, integer linear program) of your problem. Be sure to describe the meaning of each component of your formulation in words.
- Give pseudocode for the algorithms you wrote or the simulations you built to solve your problem. If you have a lot of subroutines, a flowchart may be helpful.
- Describe your experimental design: for example, how many replications of your simulation did you run?
- Describe the computing environment, the programming language, and the software that you used.

For an example, take a look at the "Building the Simulation", "Verification and Validation", and "Using the Model" sections in the following article:

J. D. Cordeiro, M. A. Friend, J. O. Miller, K. W. Bauer, J. M. Kloeber. Using simulation to model time utilization of army recruiters.Military Operations Research6(3):59-68, 2001. [link]

Discuss and interpret the results you obtained from carrying out your methodology. For this report, discussing and interpreting preliminary results is OK.

- According to your methodology, what is the solution to your problem? Don't just report raw numbers — what does the solution mean in the context of your problem?
- Carry out
**sensitivity analysis**: how does your solution change when the input parameters change? Is your proposed solution robust or sensitive to these changes? What implications does this have in the context of your problem?

For an example, take a look at the "Using the Model" section in the following article:

J. D. Cordeiro, M. A. Friend, J. O. Miller, K. W. Bauer, J. M. Kloeber. Using simulation to model time utilization of army recruiters.Military Operations Research6(3):59-68, 2001. [link]

Use this reference and citation style guide.

- Again,
**proofread, proofread, proofread.** - As usual, focus on making your report organized and well-written.

- Submitting a complete draft
- Giving a complete and correct mathematical description of your problem
- Describing your methodology thoroughly
- Presenting the (preliminary) results you obtained from your methodology, and discussing and interpreting these results in a thoughtful manner
- Writing clearly, concisely, and eloquently, and in a well-organized fashion