Statuss(Aktīvs) | Izdruka | Arhīvs(0) | Studiju plāns Vecais plāns | Kursu katalogs | Vēsture |
Course title | Mathematical Modelling |
Course code | InfT4039 |
Credit points (ECTS) | 3 |
Total Hours in Course | 81 |
Number of hours for lectures | 8 |
Number of hours for seminars and practical classes | 24 |
Independent study hours | 49 |
Date of course confirmation | 04/09/2019 |
Responsible Unit | Institute of Computer Systems and Data Science |
Course developers | |
Mg. paed., lekt. Jeļena Koroļova |
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There is no prerequisite knowledge required for this course | |
Course abstract | |
The aim of the study course is to get acquainted with Mathematical Modelling as part of the Operations Research, simulate and test systems for decision-making, acquire practical skills in Mathematical Programming (Linear Programming, Integer Programming and Integer Nonlinear Programming), modelling with MS Excel optimization tool Solver, Project Management software MS Office Project and a comparison of alternatives by The Analytic Hierarchy Process. | |
Learning outcomes and their assessment | |
After completing the course student will have:
Knowledge - about Operations Research methods for decision planning and making management with computer (tests, home works and practical works); Skills - build the mathematical models with MS Excel and MS Project for operations research and decision making with AHP (tests, home works and practical works); Competence – knowledge and ability for optimal and environmental safety decision planning and making process with Information Technologies (tests, home works and practical works). |
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Course Content(Calendar) | |
Full time intramural studies:
1. Introduction. Mathematical Programming. Classification of methods. [L- 1 h] 2. Linear programming (LP) and MS Excel Solver. Use of limited resources for profit (income) maximization. [L- 1 h ; P – 4 h] 3. Linear programming (LP) and MS Excel Solver. Use of limited resources for cost (time) minimization. [L- 1 h; P – 4 h] 4. Integer linear programming and MS Excel Solver. Optimization of the use of production resources. [L- 1 h; P – 2 h] 5. Integer nonlinear programming (INLP) with MS Excel Solver. Optimization of the use of production resources. [L – 1 h; P – 2 h] 6. 1st test (LP, IP, INLP). [2 h] 7. Network models for managing processes or projects. Critical Path Method (CPM). Project execution time risk assessment with Program Evaluation and Review Techniques (PERT). [L- 1 h; P – 2 h] 8. Linear programming in project networks for cost optimization. [L- 1 h; P – 2 h] 9. Introduction to the MS Office Project app for project or process planning. [P – 1 h] 10. 2nd test (CPM, LP networks). [2 h] 11. The Analytical Hierarchy Process (AHP) for solving engineering problems. [L- 1 h; P – 1 h] 12. The defence of individual and independent work - the application of the AHP method. [2 h] Part time extramural studies: All topics specified for full time studies are accomplished, but the number of contact hours is one half of the number specified in the calendar |
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Requirements for awarding credit points | |
Successfully passed the formal test with a grade at least 40% of the course total score. | |
Description of the organization and tasks of students’ independent work | |
Tasks for the independent work are included in e-studies (http://estudijas.llu.lv). There is one independent and individual work in the semester. | |
Criteria for Evaluating Learning Outcomes | |
1. The formal test cumulative assessment depends on two tests (70 %) and independent individual work (30 %) ratings. 2. Students who are mostly studying independently, or wish to improve the cumulative assessment take the written formal test (70 %). Independent individual work assessment (30 %) will also be taken into account. | |
Compulsory reading | |
1. Koroļova J. Lekciju konspekti, laboratorijas darbu uzdevumi un papildmateriāli. http://estudijas.llu.lv
2. Rau N. S. Optimization Principles: Practical Applications to the Operation and Markets of the Electric Power Industry. Piscataway, N.J.: IEEE Press; Wiley-Interscience, 2003. 339 p. 3. Taha H. A. Operations Research: An Introduction. 9th ed. Upper Saddle River, N.J.: Pearson Education/Prentice Hall, 2011. 824 p. 4. Moore J.H., Weatherford L.R. Decision modelling with Microsoft Excel. Prentice Hall, 2001. 1020 p. |
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Further reading | |
1. Frolova L. Matemātiskā modelēšana ekonomikā un menedžmentā. Rīga: Izglītības soļi, 2005. 438 lpp.
2. Peļņa M., Gulbe M. Optimizācijas uzdevumi ekonomikā. Rīga: Datorzinību centrs, 2003. 160 lpp. 3. Praude V., Beļcikovs J. Loģistika. Rīga: Vaidelote, 2003. 541 lpp. |
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Periodicals and other sources | |
1. E-žurnāls "Operation Research" [tiešsaiste]. Research Society of America. ISSN 0030-364X. [Skatīts 21.11.2016.] Pieejams: http://or.journal.informs.org/ | |
Notes | |
General study course for Professional Bachelor’s study program “Applied Energy Engineering” |