Optimization Software in Operational Research Analysis in a Public University.pptx

Optimization Software in Operational Research Analysis in a Public University
the usage of software in linear and non linear

1. Optimization Software in Operational Research Analysis in a Public University Kateb University Faculty of Economics MBA program Second semester Prepared by: Supervised by: Jahangir Muhammadi Dr. Najibullah Arshad

2. Presentation Agenda: 2 introduction of Operations Research Main Software for Learning Operations Research Quasi-experimental design with 80 students; 12 weeks using Invessoft vs. traditional teaching; performance tested for validity and reliability. Performance Comparison : Experimental group outperforms control group in "Achieved" levels across all dimensions. Statistical Analysis and Discussion : Non-parametric tests (Mann-Whitney U) show significant performance differences

3. Abstract 3 This research aimed to assess how the Invessoft program (using Solver, POM-QM, and Lingo) helps students solve Operations Research problems better than traditional methods. Involving 80 students from a Lima university, a quasi-experimental study showed that those using Invessoft for 12 weeks performed significantly better on a performance test compared to those using traditional methods. The findings highlight that digital tools improve problem-solving in Operations Research.

4. Introduction of OR 4 Operational Research is about creating mathematical models to solve real-world problems and find the best solutions for things like time, resources, costs, and production. It uses algorithms to help make decisions and is applied in various fields such as transportation, health, finance, manufacturing, and more. The process involves observing, collecting data, and defining the problem before solving it. Using Invessoft software (Solver, POM-QM, Lingo) improved students' problem-solving skills in Operations Research more effectively than traditional methods.

5. Main Software for Learning Operations Research 5 1. Solver (Excel Solver) Purpose: Solves optimization problems within Microsoft Excel. Scope: Linear programming (LP), nonlinear programming (NLP), integer programming (IP). Interface: Integrated into Excel, uses cells for defining models and constraints. Features: User-friendly, suitable for simpler problems, limited to Excel’s capabilities. Use Case: Quick and straightforward optimization tasks, especially for users familiar with Excel.

6. Main Software for Learning Operations Research 6 POM-QM Purpose: Provides quantitative methods for operations management and decision analysis. Scope: LP, IP, NLP, decision analysis, statistical analysis, forecasting, simulation. Interface: Standalone software with a user-friendly interface designed for educational and professional use. Features: Comprehensive suite for optimization, statistical analysis, decision analysis, and forecasting. Use Case: Educational settings, business operations analysis, and decision-making.

7. Main Software for Learning Operations Research 7 LINGO Purpose: Specialized optimization software for a wide range of optimization problems. Scope: LP, NLP, IP, mixed-integer programming (MIP), advanced modeling . Interface: Provides a dedicated modeling language and GUI for problem definition. Features: Advanced modeling capabilities, supports large and complex problems, detailed sensitivity analysis. Use Case: Complex and large-scale optimization problems, academic research, and professional consulting.

8. Quasi-experimental design with 80 students 8 Groups : 40 students in each group—one used Solver, POM-QM, and Lingo software (experimental), the other did not use any software (control). Procedure : Both groups, with no prior software use, were tested on optimization problems at the end of the semester. The test, validated by experts, covered four topics and had yes/no questions. Data Analysis : Results were analyzed using SPSS software. Students gave consent through Google Drive due to COVID-19.

9. Performance Comparison 9 Groups : The experimental group used software tools, while the control group did not. Key Findings : Linear Programming : The experimental group performed better at the end of the course (52.5%) compared to the control group (20%). Waiting Queue : The experimental group showed much higher achievement (70%) compared to the control group (15%). Project Management : The experimental group excelled at the end (67.5%) versus the control group (30%). Forecasts : The experimental group had more than double the achievement rate (65%) compared to the control group (30%). Overall : The experimental group showed greater improvement in solving problems by the end of the course. Initially, the control group performed better, but as the experimental group learned to use the software, their performance improved significantly.

10. 10 Various studies confirm that using software enhances teaching and learning in Operational Research courses. For example: Pérez & Ramírez (2019) : Students using WinQSB and Solver software performed better than those using traditional methods. Cavallin et al. (2017) : Using POM-QM software increased student interest in Operational Research. Sousa (2014) : The LOpt Calculator significantly helped in learning linear optimization. Ávila (2019) : A simple software prototype for linear programming made the subject more engaging. Ferreira (2015) : The Simplex algorithm was implemented in an Excel VBA program, aiding in learning. . Statistical Analysis and Discussion :

11. 11 The research highlights that using computer tools is crucial for industrial engineering students to solve optimization problems effectively. With software, students not only improve their skills but also become more interested in Operations Research, leading to fewer failures. The shift to virtual classes due to the pandemic has made digital tools even more important. Overall, using software for building mathematical models has proven to be more effective than manual methods, and this study helps enhance the teaching and learning of Operations Research Conclusion

12. 12 The company "Protection" belongs to the production sector, which is dedicated to the manufacture of two products that are sold in its different stores in Lima, very useful to avoid the greater risk of being infected with COVID-19; the company manufactures face shields and overalls. Based on a study carried out by the Ministry of Health of Peru, the current inventories and in the face of the exponential demand for this new wave of infections, the “Protection” company is forced to increase its combined production between face shield and overalls, these they must total at least 450 units. On the other hand, it must also supply the order of 250 face shields and 136 overalls at least respectively, to the district of Lima with the highest risk of contagion; the face shield takes 6 minutes to manufacture, while the overalls require about 30 minutes to manufacture; in addition, for the following week, there is 100 hours of manufacturing time. The objective of the company "Protection" is to achieve the manufacture of these products with minimum costs to supply the Peruvian population. Production costs are $ 0.5 for the face shield and $ 5 for the overalls. Example

13. Thank you for your time! 13