Universidad Pública de Navarra - Nafarroako Univertsitate Publikoa
Public University of Navarre
| Course code: 176305 | Subject title: OPTIMIZATION THEORY/QUANTITATIVE METHODS OF BUSINESS MANAGEMENT | ||||
| Credits: 6 | Type of subject: Mandatory | Year: 2 | Period: 1º S | ||
| Department: Estadística, Informática y Matemáticas | |||||
| Lecturers: | |||||
| FAULIN FAJARDO, FCO. JAVIER (Resp) [Mentoring ] | AGUSTIN MARTIN, ALBA MARIA [Mentoring ] | ||||
Contents
This subject presents a classical content of Linear Programming applied to decision making in Management. The typical models that will be introduced here will be: Linear Programming, Integer and Multicriteria Programming, with application to decision makings in Production, Marketing, Finance, Human Resources, and Strategy. It is highlighted the use of exact methods for the resolution of linear programs and practical cases related to real companies. The practical point of view will be essential in the development of this subject.
General proficiencies
CG01. Capacity of Analysis
CG02. Capacity of Organization and Planning
CG04. Communication Skills in Foreign Languages
CG05. Computer Skills
CG06. Ability of Analyzing and Searching Information from different sources.
CG07. Capacity of Solving Problems
CG08. Capacity of Making Decisions.
CG09. Capacity of working in a team.
CG10. Working in an interdisciplinary team.
CG11. Working in an international context.
CG13. Capacity of working in diverse and multicultural scenarios.
CG14. Critic and Autocritic Capacity.
CG15. Ethical Commitment at the Work.
CG17. Capacity of autonomous learning.
CG18. Capacity of adapting to new situations.
CG19. Creativity.
CG21. Entrepreneurship Spirit and Leadership.
CG23. Sensitivity towards environmental and social topics.
Specific proficiencies
SP01 Understand economic institutions as a result and application of theoretical or formal representations about how the economy works.
SP02 Identify the sources of relevant economic information and their contents.
SP03 Derive from microeconomic and macroeconomic data the data and relevant information impossible to recognize for non-professionals.
SP04. Apply professional criteria based on the handling of technical instruments to the analysis of business management problems.
SP05 Issue advisory reports on specific situations of companies and markets.
SP06. Write projects on global management or on functional areas of the company.
SP07 Assess the situation and foreseeable evolution of a company from the relevant records of information.
SP11 Understand the nature of the company as an organization and place of interaction of agents with different interests.
SP13 Identify the company as a system and recognize the interdependencies between the different functional areas.
Learning outcomes
RE1) Developed knowledge of the use of mathematical models to make decisions.
RE2) Good understanding of the meaning of the use of algorithms to solve mathematical problems related to Business problems
RE3) Good applications skills of the use of quantitative methods in decision making in real problems in the different subsystems of the firm: Marketing, Production, Finance, Information Analysis, and Human Resources.
RE4) Development of the Analysis that the student can perform of one specific area of the firm using Quantitative Methods.
RE5) Summary and synthesis skills to evaluate the results of a quantitative model to make decisions in a company.
Methodology
| Training activity | Methodology | Hours |
| Theoretical sessions at the classroom | The instructor will develop the topic objectives, its contents, and problems, highlighting the most difficult ones related to the unit to be explained. | 30 |
| Study of the theoretical sessions | Reading of a short text related to the topic to study | 03 |
| Weekly own study | Own study of the topics explained in the theoretical classes. | 35 |
| Practical classes at the classroom | Development of practical exercises to be developed with the use of a computer. | 30 |
| Assignments writing | Development of assignments to be given in to the instructor and could be discussed in class. | 25 |
| Consulting activities | Presentation and discussion of the problems and difficulties found in the subject | 01 |
| Exam | Study and development of the subject exams | 26 |
| Total | 150 |
Evaluation
| Learning outcome | Evaluation Method | Weight (%) | Recoverable |
| Problems Resolution of Decision Making Processes in Companies | Final Exam | 75 | Yes |
| Problems Resolution of Decision Making Processes in Companies | Practical cases - Final exam | 15 | No |
| Problems Resolution of Decision Making Processes in Companies | Midterm exams | 25 | No |
| IMPORTANT INFORMATION ABOUT MINIMUM SCORING TO PASS THE EXAMS | Scoring |
| Midterm exam: 25% (Students who do this exam cannot have the NO PRESENTADO mark) | TOTAL SCORE: 115% Minimum score to pass the subject: 60% |
Important information about the subject:
- There are two calls for the final exam. All the students registered at the subject have to do the final exam in the first session to be candidates to pass the subject. If a student fails the final exam in the first call and does not pass the subject either, s/he can only attend the second call of the final exam if her/his mark in the first final exam has been at least 35% out of the total score of the final exam. That is to say, the student having not a minimum mark of 35% out of total score in the first exam cannot attend the second call of the final exam.
- Only it is possible to compensate all the marks presented in the previous table if the student has obtained a minimum mark of 40% out of the total score in the final exam. That is to say, a student obtaining a mark below 40% in the final exam cannot pass the subject.
Agenda
Chapter 1: Introduction to Quantitative Methods and Business Analytics.
Chapter 2: An Introduction to Linear Programming.
Chapter 3: Linear Programming: Sensitivity Analysis and Interpretation of Solution.
Chapter 4: Linear Programming Applications.
Chapter 5: Linear Programming: The Simplex Method.
Chapter 6: Advanced Linear Programming Applications.
Chapter 7: Simplex-Based Sensitivity Analysis and Duality.
Chapter 8: Transportation, Assignment, and Transshipment Problems.
Chapter 9: Integer Linear Programming.
Chapter 10: Multicriteria Decisions.
Chapter 11: Applications of Linear Programming, Integer Programming and Multicriteria Programming in real cases in companies
Bibliography
Access the bibliography that your professor has requested from the Library.
Main References:
1) Anderson, D.R., Sweeney, D. J., Williams, T.A. Camm, J. and Martin, K. (2012): An Introduction to Management Science. Quantitative Approach to Decision Making. West Publishing Company. (ASW) (Main handbook)
Complementary References:
2) Hillier, F.S. and Hillier, M.S. (2011): Introduction to Management Science. A Modeling and Case Studies Approach with Spreadsheets. McGraw-Hill. (HH)
3) Hillier, F.S. and Liebermann, G.J. (2010): Introduction to Operations Research. McGraw-Hill. (HL)
4) Lawrence, A.L. and Pasternack, B.A. (2002): Applied Management Science. A Computer Integrated Approach for Decision Making. Wiley. (LP)
5) Powell, S.G. and Baker, K.R. (2009): Management Science. The Art of Modeling with Spreadsheets. Wiley. (PB) 6) Winston, W. (2005): Operations Research. Applications and Algorithms. Duxbury. (WW)
Languages
English. A C1 level of English is recommended to follow this subject. Students not fulfilling the C1 requirement could have problems to follow this subject.
Location
Room for theoretical classes, computer rooms, and virtual course Mi Aulario. Roughtly speaking, the 80% of the teaching will be done in a room and the 20% in the virtual course Mi Aulario.