Quantitative Methods
Objectives
At the end of this course unit the students will have acquired knowledge, skills and competencies to achieve the following objectives:
O1: Correctly analyze and dimension queueing systems (with and without limitations of capacity and population);
O2: Analyze and support optimization of productive network flows;
O3: Properly formulate and solve production problems through dynamic programming;
General characterization
Code
10580
Credits
6.0
Responsible teacher
Alexandra Maria Batista Ramos Tenera, Ana Paula Ferreira Barroso
Hours
Weekly - 4
Total - 68
Teaching language
Português
Prerequisites
Is advised that students have some expertise in Statistics and Operations Research
Bibliography
- Hillier, F. & Lieberman, G. (2010). Introduction to Operations Research (9th ed.). USA, Mcgraw-Hill. or Taha, H. (2010). Operations Research: An Introduction (9th ed.) Englewood Cliffs, Prentice Hall.
- Evans, J. & Minieka, E. (1992). Optimization Algorithms for Networks and Graphs (2nd ed.). USA, Marcel Dekker, Inc.
- Lapin, L.(1994). Quantitative Methods for Business Decisions with Cases (6nd ed.). USA, Dryden Press.
- Chang, Y-L (2003) WinQSB: Decision Support Software for MS/OM Version 2.0. USA, John Wiley & Sons.
- Bronson, R & Naadimuthu, G. (2001). Investigação Operacional (2ª ed.). Trad. Ruy Costa. Alfragide, Mcgraw-Hill de Portugal, Lda.
Teaching method
Lectures are carried out combining theoretical classes and applied ones. In theoretical classes,a summary of the subjects that will be discussed is presented. Concepts models are explained, discussed and applied, stimulating the student participation during their presentation. In the end of the lecture, the most relevant aspects are highlighted as well as the main subjects for the following lecture,encouraging students to study the subjects before there discussion.
In practical classes,exercises and case studies are analyzed and discussed.To develop and improve other competences and capacities, the students must also carry out,computer analyzes and work reports which must also be discussed and supported
Evaluation method
Students’ assessment is made as follows: Group Evaluation-GE as well as Individual Evaluation(IE) by Exam(EX)or Tests(Mid Test(T1)and at the end of the semester(T2).
If Tests Average (TA)>=9.0 no Exam is required
GE used to obtain course unit frequency (Freq=1if GE>=9,5).
Final Grade (FG)=0.4GE+ 0.6 EX (or Ts average).
Subject matter
1. Queueing Theory: Basic Structures; Terminology and Notation; Main Performance Measures; Little’s Equations; Deterministic and Probabilistic Models with Exponential distributions and FIFO discipline; Multiple servers; Finite queue and finite calling population variation; Data Analysis and Goodness Fit Tests;
2. Graphs and Network Analysis: Minimum Spanning Tree; Shortest-Path; Maximum Flow; Transportation; Assignment and Transshipment Problems;