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SYDE-411

Project Guidelines

SYDE 411 Optimization and Numerical Methods

Project Guidelines

This group project involves searching for a real-world engineering optimization problem by you, which is formulated mathematically, then solved and analyzed by applying a suitable optimization technique, which is implemented in MATLAB or Python. As described below, a presentation is required, in addition to submitting a final report and related MATLAB or Python code.

Important Notes:

  1. The optimization problem you choose should be multivariable with some constraints such that applying optimization techniques is needed to solve it, and finding a solution without computer programming/software tools is very hard. A one-page proposal focusing on a general description of the considered problem should be submitted through a Dropbox folder on LEARN by Friday, Oct. 21.
  2. A proper set of design variables should be selected, and the objective function and constraints should be formulated accordingly in a mathematical programming form. The problem will then be solved by implementing a proper optimization algorithm, or using an optimization toolbox, in MATLAB or Python (using another software package or computer programming is possible by permission). Finally, the results should be analyzed by considering the nature of the solution (local or global optimum), selected optimization technique performance (convergence, computational speed, etc.), characteristics of the problem like its feasible region, unimodality, convexity, continuity, and so on. Deliverables:
  3. A Powerpoint presentation with three main slides on: i) problem description, ii) formulation and optimization method, and iii) some results/analyses. The presentation time will be: “5 minutes for the slides” plus “3 minutes for Q&A” (totally, 8 minutes). More information about the presentations (dates, order, etc.) will be given later.
  4. A technical report (main body less than ten pages, having an appendix is acceptable), including the problem description, modeling & formulation, assumptions, choice of applied optimization technique, results, analyses, conclusions, and suggestions for future steps. A soft copy of the report and MATLAB or Python files should be submitted through a Dropbox folder on LEARN. The project report/files should be submitted by Tuesday, Dec. 6.

Evaluation:

Please note that the following factors will be taken into account for marking the project report:

  • Proper background, motivation, and context for the selected optimization problem.
  • Clarity and validity of the problem description, formulation, constraints, objective function, feasible region, etc.
  • Using a suitable method (and the related logic) to solve the problem, properly implementing the technique for the given problem formulation and a clear explanation or flowchart for this process.
  • Clarity, validity, and justification of solutions/results.
  • Mindful discussions of convergence and computational efficiency of the optimization method, discussing the nature of solution (global or local) and related justifications, convexity, unimodality/multimodality of the objective function, constraint satisfactions, the effects of initial guess (when a numerical method is used), any other thoughtful explanations from an optimization perspective.
  • Level of complexity of the considered problem, including the number of constraints and optimization variables, objective function form, discontinuity, multimodality, etc.
  • Any innovation in the optimization formulation or methodology to solve the selected optimization problem. Using optimization techniques that are not covered in the course is possible through permission/consultation with the instructor.
  • Report format/structure, figure qualities, grammar, conclusions & suggestions for future steps, etc. Please note this is a group project and requires the participation of all group members for the entire tasks. If you need further information, please don’t hesitate to contact the instructor. Enjoy your project!