Fall 2021 Project Guidelines
The purpose of this project is to provide students with a hands-on experience in solving real life problems using Operations Research (OR) techniques covered in class. The reasoning behind emphasizing on the “practicality” of the problem being addressed in this project is to appreciate the value and importance of the OR techniques and how they help solving real life optimization problems. You are invited to select a problem obtained from the industry sector, whether locally or internationally, or from the service sector, i.e., hospitals, universities, banks, real estate, airlines, etc. In the case where a practical problem cannot be identified, a thorough analysis of a typical, but rather involved, case study might be accepted.
The objectives of the project should be stated in clear terms. More specifically, what are the potential improvements that the project strives to achieve with respect to the current strategy being employed? How would the project outcomes contribute to the financial status of the organization and how valuable such contributions are? In other terms, if the organization is not utilizing LP techniques towards improving their operations, what is it that they might be overlooking or losing by ignoring such a useful tool?
The following is a suggested layout for the project report.
Introduction: General introduction to the importance of the project, the tools used and the relevance of LP techniques to the current project and brief Company overview.
Problem description: Current operating conditions, status of the business, potential areas of improvement, where are they now and where do they want to get. What exactly is the problem that the project is trying to solve, and how does the solution help towards meeting the company’s long term objectives.
Brief Literature review: of similar problem. The objective is to find similar problems and their formulations.
Data collection: Once the problem has been identified, students are expected to collect relevant data for the model inputs or parameters (e.g., the availability of resources, the usage rates of the resources for each product (constraints coefficients) and objective function coefficients). If such data is not available or if there were any assumptions made in order to come up with the necessary data, this should also be clearly stated.
Modeling considerations and assumptions: Which aspects of the problem have been addressed and which other aspects have not. In many cases, the problem might be too complicated to explore in full scale and hence there might be a need for simplifying assumptions in order to make it tractable. The assumptions you make during your work are particularly important to the validity of the mathematical model developed at a later stage.
The mathematical model: This is the core of the project and substantial efforts should be directed towards perfecting the formulation of the mathematical model. In particular, the decision variables used, the objective function and each constraint shall be clearly defined so that the report is reader friendly and the model is easily understandable.
Solution procedure (Computer implementation): Once the problem at hand is formulated, solve the model using Excel solver or GAMS. The choice of which software to use is entirely yours as long as such implementation is detailed clearly in the report with screen snapshots.
Output analysis: The output obtained from the computer software shall be reported in full.
This includes the optimal values of the decision variables and the objective function, the interpretation of the dual values and the reduced costs, the binding and non-binding constraints at optimality, the range of feasibility as well as the range of optimality.
Post-optimality and what-if analysis: It is of great importance to include post-optimality analysis and what if analysis. For instance, what would be the impact of changing the right hand side of the constraints (i.e., what would happen if the company manages to get more of a certain resource and what is the maximum amount that should be paid per unit of that resource)? How would changes in the cost/profit coefficients affect the current optimal solution and would an investment in new machinery, for instance, be justified by the obtained cost reductions?
Extensions to incorporate (if any): This studies the effect of incorporating in the mathematical model some of the previously relaxed restrictions. For example, what happens if we allow overtime or if there is a budget constraint, or a warehouse capacity restriction? Basically, any extension to the basic model that would enhance its applicability should be investigated.
Conclusion: A summary of the analysis that has been done, technical difficulties faced during the project and the Learning outcomes of the project.
Appendices (If any): Include any explanatory figures, charts, diagrams, or tables of data collected and used in the model.
Project Submission and Presentations:
Phase 1: Problem Description/Literature Review 20%
Phase 2: Problem Formulation and Data Collection 30%
Phase 3: Final Report 30%
Phase 4: Presentation 20%
Complete the assignment up to here, based on your performance for this part you might be assigned for the rest.
Grammarly for order editing
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