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Lecturer(s)
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Munzarová Simona, Ing. Ph.D.
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Course content
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1st week: Introduction to modeling. Characteristics of operation research: system approach, team work, computer usage. 2nd week: Basic models for problem of balancing production. Specifics of multi-stage chemical productions. 3rd week: Cost Input-Output models and their usage for product and semifinished product cost calculations in multi-stage chemical productions. 4th week: Linear Programming. Formulating LP Models. Different approaches to solve LP problems. 5th week: Building LP models in spreadsheet conditions. 6th week: Use of LP modelling for production and human resource planning purposes. 7th week: Use of LP modelling for solving some distribution problems. 8th week: Graph theory, building network models in MS Excel. 9th week: Resources and cost optimization using network models. 10th week: Equipment Replacement Problems using network models. 11-12th week: Spreadsheet modelling for solving supply chain problems. 13th week: Building own model on choosen topic.
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Learning activities and teaching methods
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unspecified, Dialogic (discussion, interview, brainstorming), Work with text (with textbook, with book), Methods of individual activities
- Contact teaching
- 39 hours per semester
- Writing a seminar paper
- 30 hours per semester
- Preparation of a presentation (report)
- 20 hours per semester
- Preparation for an exam
- 35 hours per semester
- Home preparation for classes
- 25 hours per semester
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Learning outcomes
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The course focuses on mathematical modeling and optimization of complex managerial decision problems in business economy and operations management. The course follows up Math and Statistics classes, and develops, deepens and integrates knowledge in business economy and other economy-managerial classes. In seminars, students practice different methods solving examples using PC and MS Excel. Attention is paid to the interpretation and implementation of models in practice.
Students gain the skills to formulate managerial decision problems as mathematical models, gain the ability to choose appropriate methods for their solution and to find optimal respectively effective solutions using Excel and to interpret the obtained results, including sensitivity analyzes.
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Prerequisites
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A prerequisite for studying the subject is knowledge of mathematics, business economics and business management at the undergraduate level.
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Assessment methods and criteria
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Oral examination, Didactic test, Self project defence, Presentation
Knowledge and skills are verified by written and oral exam. It examines the rate of acquired knowledge and application skills.
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Recommended literature
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Albright, S. C., Winston, W. L. Management Science Modeling, 3rd edition, South-Western Cengage Learning, ISBN 0-324-66346-3.
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Anderson, Sweeney, Williams, Camm, Martin. Quantitative Methods for Business, 12th edition, South-Western Cengage Learning, ISBN 1-133-58446-2.
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Render, B., Stair, R. M. Jr., Hanna, M. E. Quantitative Analysis for Managers, ninth edition, Pearson, Prentice Hall, 2006, New Jersey ISBN 0-12-153688-5.
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