To complement and deepen the theoretical knowledge and practice of Decision Support Techniques. This curricular unit follows the study of Operational Research Techniques initiated in the 3rd year of the MIEGI study plan, with emphasis on decision making in stochastic contexts.
To deepen the study of methods of Problem Structuring and Analysis, in order to solve real-world problems in organizations. Particular emphasis is given to aspects related to Markov Chains, Queueing Systems and Visual Interactive Simulation. An introduction to Multicriteria Decision Making is also provided.
To promote and deepen interpersonal skills, especially group work and communication skills.
Learning outcomes and competences
This course promotes the acquisition of the following competences:
To deal with complex decision-making situations using quantitative methods;
To identify and select the operational research techniques that are best suited to solve concrete problems in organizations;
To master the algorithmic and computational aspects associated to the techniques of Operational Research studied in this course;
To work and cooperate as a team.
Working method
Presencial
Pre-requirements (prior knowledge) and co-requirements (common knowledge)
Operational Research Statistics
Program
1. MARKOV CHAINS: Transition matrix of a Markov Chain. Analysis of ergodic chains and absolving chains. Generalisations.
2. QUEUING THEORY: Characterisation of queuing processes. The M/M/1 queuing system. Queuing systems with more than one server. Finite source models and systems with limited capacity. Priority queuing models.
3. SIMULATION: Objectives and limitations. Event, activities and process-based approaches to discrete simulation. Fundamental concepts (entities, queues, etc.). Development of models. Introduction to Arena Software and application to case-studies.
4. MULTICRITERIA DECISION MAKING: Decision problems with multiple objectives. Goal Programming. Analytic Hierarchy Process (AHP).
Mandatory literature
Ana Camanho; Slides de apoio às aulas da unidade curricular Investigação Operacional II, 2017
Ana Camanho; Problemas propostos da Unidade Curricular Investigação Operacional II , 2017
Ana Camanho; Resolução dos problemas propostos da unidade curricular Investigação Operacional II
Kelton W. David; Simulation with Arena. ISBN: 978-1-259-25436-9
Manuel D. Rossetti; Simulation Modeling and Arena
This course combines lectures covering Operational Research methods and techniques, problem solving classes (some in computer labs), and classes to present and discuss case studies solved by student groups.
Software
Arena
keywords
Physical sciences > Mathematics > Applied mathematics > Operations research
Social sciences
Evaluation Type
Distributed evaluation with final exam
Assessment Components
Designation
Weight (%)
Exame
65,00
Teste
10,00
Trabalho prático ou de projeto
25,00
Total:
100,00
Amount of time allocated to each course unit
Designation
Time (hours)
Elaboração de projeto
34,00
Estudo autónomo
86,00
Frequência das aulas
42,00
Total:
162,00
Eligibility for exams
According to the "General Evaluation Rules" of FEUP Pedagogical Council
Calculation formula of final grade
Formula for the Calculation of the Final Classification: Final Classification = 0.65*EF + 0.10*MT + 0.25*(0.75*AG+0.25*(AG+OI)).
Being: EF: final exam MT: test of the Simulation topic. AG: Evaluation of the Group - Evaluation of the work done by the group in the Arena software, based on the quality of the model implemented in Arena, the report produced and the oral presentation of the work (0 to 20 scale). OI: Offset_Individual - Individual performance within the team, whose grade is attributed by the teachers of the course, based on the average of the evaluations given by the peers (other members of the group). This individual offset can range between ± 2. The sum of the Offset_Individual for all elements of a team must be between -1 and +1
The approval to the Curricular Unit (course) requires obtaining a ranking of 7.5 or higher in the Simulation group work (AG + OI) and in the final exam.
In the exam of appeal, the weights of the exam (EF), the test on Simulation (MT) and the group work used in calculating the final classification are identical to those of the normal exam period.
Examinations or Special Assignments
A Case Study prepared by groups of students, with the production of a final report and presentation.
The contents of the Simulation topic, evaluated in the Case Study and in the test, will not be evaluated in the final exam.
Internship work/project
Not applicable.
Special assessment (TE, DA, ...)
For students with special status and conditions (Students' Union Leaders, High Performance athletes, students with special educational needs) the weights used for the calculation of the final classification is equal to weights used for all other students (the weight of the exam is 65% , the weight of the group work is equal to 25%, and the weight of the minitest on the simulation topic is equal to 10%).
Classification improvement
The students can repeat the exam in the period of appeal, but there is no possibility of repetition of the evaluation component regarding the group work and test on the simulation topic.
Students wishing to improve their final classification may also do so in the following academic year. The grade of the group work and the simulation test will be considered identical to the previous academic year in the case of repetition of the exam in the following academic year.