Operations Research
Code: 104685 ECTS Credits: 6| Degree | Type | Year |
|---|---|---|
| 2501572 Business Administration and Management | OB | 3 |
| 2501573 Economics | OT | 3 |
| 2501573 Economics | OT | 4 |
Contact
- Name:
- Gabriela Sicilia Suárez
- Email:
- gabriela.sicilia@uab.cat
Teachers
- Claudia Sanguinetti
Teaching groups languages
You can view this information at the end of this document.
Prerequisites
Those established by the current public regulations for university degree studies.
Objectives and Contextualisation
This course is an introduction to Operations Research for students in Business Administration. The course provides basic tools for modeling and to make scientifically based economic decisions. Throughout this course, students are expected to know how to formulate problems as quantitative models that can be solved using algorithmic procedures. Also, students will be able to understand and interpret the results of these procedures.
Competences
- Business Administration and Management
- Apply mathematical instruments to synthesise complex economic-business situations.
- Apply theoretical knowledge to improve relations with clients and suppliers, identifying the advantages and disadvantages of those relations for both sides: company and client or supplier.
- Capacity for independent learning in the future, gaining more profound knowledge of previous areas or learning new topics.
- Identify, justify and reason the appropriate decisions according to the basic parameters of a business problem.
- Select and generate the information necessary for each problem, analyse it and take decisions based on that information.
- Take decisions in situations of uncertainty, demonstrating an entrepreneurial and innovative attitude.
- Use of the available information technology and adaptation to new technological environments.
Learning Outcomes
- Apply algorithmic resolution techniques to optimisation problems.
- Apply the basic principles of modelling in business decision-making.
- Capacity to continue future learning independently, acquiring further knowledge and exploring new areas of knowledge.
- Differentiate between alternative methods of analysis, and apply the appropriate quantitative tools to resolve business management problems.
- Make decisions in situations of uncertainty and show an enterprising and innovative spirit.
- Select and generate the information needed for each problem, analyse it and make decisions based on this information.
- Solve problems optimising and obtaining forecasts through information technology applications.
- Use available information technology and be able to adapt to new technological settings.
Content
CONTENTS
PART I
INTRODUCTION TO LINEAR PROGRAMMING
1.1 Introduction to Operations Research: principles and methods
1.2 Fundamentals of Mathematical Programming. Continuous linear problems: the simplex algorithm. Sensitivity Analysis.
1.3 The transportation problem. Assignment and matching problems. Integer problems
1.4 Software for the resolution of mathematical programming problems by numerical methods
PART II
INTRODUCTION TO GRAPH THEORY AND NETWORK FLOWS
2.1 Fundamentals and basic concepts. Paths, circuits, chains, cycles, trees, forests and networks
2.2 Optimal spanning trees
2.3 Optimal paths in a network. Maximum flows. Analysis of social networks
2.4 Software for the resolution of network optimization problems by numerical methods
Activities and Methodology
| Title | Hours | ECTS | Learning Outcomes |
|---|---|---|---|
| Type: Directed | |||
| Problem solving classes | 17 | 0.68 | |
| Theory classes | 32.5 | 1.3 | |
| Type: Supervised | |||
| Supervised | 6.5 | 0.26 | |
| Type: Autonomous | |||
| Autonomous | 90 | 3.6 |
1. Theoretical lectures.
2. Practice classes: modeling and solving problems and learn algorithmic techniques.
3. Individual study based on the material developed in the lectures and in the complementary references.
Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.
Assessment
Continous Assessment Activities
| Title | Weighting | Hours | ECTS | Learning Outcomes |
|---|---|---|---|---|
| Evaluative test | 25% | 1 | 0.04 | 2, 1, 3, 4, 5, 7, 6, 8 |
| Final exam | 50% | 2 | 0.08 | 2, 1, 3, 4, 5, 7, 6, 8 |
| Practical project | 25% | 1 | 0.04 | 2, 1, 3, 4, 5, 7, 6, 8 |
This subject/module does not offer the option for single evaluation.
Evaluation criteria
The evaluation criteria follows the new Model of Academic Dedication (article 9.2) approved by the Governing Council on December 13th, 2017 and by article 112bis of UAB Academic Regulations approved by Governing Council on July 12th, 2017.
Continuous assessment
The evaluation of the subject will be carried out considering the following criteria:
1. Practical work, carried out in groups of 2 to 5 students, to be delivered in pdf format through the virtual campus. 25% of the final grade.
2. Partial test: 25% of the final grade.
3. Final exam: 50% of the final grade. All the contents of the subject are evaluated.
Additional Information
• It is necessary to obtain a minimum of 4 in the final exam to pass the subject.
• Students who obtain a final grade equal to or greater than 5 points, having obtained at least a 4 in the final exam, will pass the subject.
• Students who obtain a final grade between 3.5 points and 5 points, or who having obtained a final grade equal to or greater than 5 points, but scored below 4 points in the final exam, may take the recovery exam. The teachers of the subject will decide the modality of the recovery exam, which will be common to all students. Students who take the recovery exam and pass it (that is, they score 5 or more points) will obtain a final grade for the subject of 5 points. Otherwise, they will maintain the final exam grade.
• Students who obtain a final grade of less than 3.5 points will not be able to take the recovery exam and will have to repeat the subject.
• The student will have the final grade of "absent" when he/she has not participated in any of the evaluation activities.
Retake Process
"To be eligible to participate in the retake process, it is required for students to have previously been evaluated for at least two thirds of the total evaluation activities of the subject." Section 3 of Article 112 ter. The recovery (UAB Academic Regulations). Additionally, it is required that the student to have achieved an average grade of the subject equal to or greater than 3.5 and less than 5.
The date of the retake exam will be posted in the calendar of evaluation activities of the Faculty. Students who take this exam and pass, will get a grade of 5 for the subject. If the student does not pass the retake, the grade will remain unchanged, and hence, student will fail the course.
Calendar of evaluation
“The dates of the evaluation activities (midterm exams, exercises in the classroom, assignments, ...) will be announced well in advance during the semester. The date of the final exam is scheduled in the assessment calendar of the Faculty.
The dates of evaluation activities cannot be modified, unless there is an exceptional and duly justified reason why an evaluation activity cannot be carried out. In this case, the degree coordinator will contact both the teaching staff and the affected student, and a new date will be scheduled within the same academic period to make up for the missed evaluation activity. Section 1 of Article 115. Calendar of evaluation activities (Academic Regulations UAB). Students of the Faculty of Economics and Business, who in accordance with the previous paragraph need to change an evaluation activity date must process the request by filling out an Application for exams' reschedule https://eformularis.uab.cat/group/deganat_feie/nou-reprogramació-de-proves
Grade revision process
“After all grading activities have ended, students will be informed of the date and way in which the course grades will be published. Students will also be informed of the procedure, place, date and time of grade revision following University regulations.”
Irregularities in evaluation activities
In spite of other disciplinary measures deemed appropriate, and in accordance with current academic regulations, "in the case that the student makes any irregularity that could lead to a significant variation in the grade of an evaluation activity, it will be graded with a 0, regardless of the disciplinary process that can be instructed. In case of various irregularities occur in the evaluation of the same subject, the final grade of this subject will be 0". Section 10 of Article 116. Results of the evaluation. (UAB Academic Regulations).
Bibliography
Basic bibliography
Pujolar, D. (2022): http://rt003ydd.byethost33.com
Further reading (latest editions)
Bazaraa, M.; Jarvis, J. and Sherali, H. (2010): Linear Programming and Network Flows 4th ed. Wiley; chs. 1-4; 10 and 12.
Hillier, F. and Lieberman, G. (2020): Introduction to Operations Research, 11th ed. McGraw-Hill; chs. 1-5; 9-10 and 12.
Newman, M. (2018): Networks: An Introduction, 2nd ed. Oxford University Press; chs. 1-6; 9-10.
Schrage, L. (2006): Optimization Modeling with LINGO, 6th ed. LINDO Systems Inc; chs. 1-2 and 5.
Wilson, R. J. (2010): Introduction to Graph Theory. 5th ed. Thomson; chs. 1 and 3.
Lecturers can recommend different bibliography in their own groups, in exercise of their academic freedom. Changes will be communicated to students in the first lecture.
Software
LINGO and others.
Language list
| Name | Group | Language | Semester | Turn |
|---|---|---|---|---|
| (PAUL) Classroom practices | 2 | Spanish | first semester | morning-mixed |
| (PAUL) Classroom practices | 4 | English | first semester | morning-mixed |
| (PAUL) Classroom practices | 52 | Spanish | first semester | afternoon |
| (PAUL) Classroom practices | 60 | Spanish | first semester | morning-mixed |
| (TE) Theory | 2 | Spanish | first semester | morning-mixed |
| (TE) Theory | 4 | English | first semester | morning-mixed |
| (TE) Theory | 52 | Spanish | first semester | afternoon |
| (TE) Theory | 60 | Spanish | first semester | morning-mixed |