Operations Research

Code:

EEC0017

Acronym:

IOPE

Keywords
Classification	Keyword
OFICIAL	Mathematics

Instance: 2009/2010 - 1S

Active?	Yes
Web Page:	http://www.fe.up.pt/~mac/ensino/IO20092010.html
Responsible unit:	Department of Industrial Engineering and Management
Course/CS Responsible:	Master in Electrical and Computers Engineering

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MIEEC	174	Syllabus since 2007/2008	3	-	6	63	160

Teaching language

Portuguese

Objectives

1 - BACKGROUND
This course builds on optimization and provides the student with advanced modeling and optimization tools that will be useful in a variety of industries and functions.
2 - SPECIFIC AIMS
The primary objective of this course is to develop the capacity to generate insights via modeling in a variety of realistic situations. This capacity builds mainly on the ability to recognize the key problem in a situation and on the ability to develop a structure for analyzing and tackling the problem.
3 - PREVIOUS KNOWLEDGE
Basic courses on Algebra and Statistics
4 - PERCENT DISTRIBUTION
Scientific Component - 70%
Technological Component - 30%
5 - LEARNING OUTCOMES
Endow the students with competences to:
- identify and approach decision problems in a structured way;
- build models for decision problems;
- use quantitative methods to obtain solutions for models;
- use spreadsheets for the models analysis and solution generation;
- begin to use the information extracted from the models to induce and motivate organizational changes.

Program

Introduction to Operational Research (OR)
Decision Analysis
Modeling
Linear Programming (LP)
LP – Simplex algorithm
Integer Programming
Networks and Graphs:
- Transportation problems
- Assignment problems
- Maximum flow and Shortest path
- Project planning and control, CPM and PERT
Queuing systems
Statistical and Discrete Simulation

Mandatory literature

Hillier, Frederick S.; Introduction to operations research. ISBN: 0-07-118163-6

Complementary Bibliography

Antunes, Carlos Henggeler 340; Casos de aplicação da investigação operacional. ISBN: 972-773-075-2
Tavares, Luís Valadares 070; Investigação operacional. ISBN: 972-8298-08-0
Clemen, Robert T.; Making hard decisions. ISBN: 0-534-92336-4

Teaching methods and learning activities

Theoretical classes: presentation of the themes of the course illustrated by cases, examples and problems

Practical classes: Students can clarify possible doubts about problems and homework

Software

Solver do Excel

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Description	Type	Time (hours)	Weight (%)	End date
Subject Classes	Participação presencial	56,00
Homework and assignments	Teste	15,00		2010-01-06
Final Exam	Exame	20,00		2010-02-12
	Total:	-	0,00

Amount of time allocated to each course unit

Description	Type	Time (hours)	End date
Self study	Estudo autónomo	71	2010-02-12
	Total:	71,00

Eligibility for exams

Article 4 of General Evaluation Rules of FEUP
Students have to reach a minimum grade of 40% in the continuous assessment component.

Calculation formula of final grade

Homework and exercises- from 0 to 7 values (minimum of 3 values)
Final Exam (open book) – from 0 to 13 values (minimum of 40)

Examinations or Special Assignments

During the semester, students will be asked to do 4 homework exercises with a deadline.
The homework is to be done individually and handwritten and cannot exceed an A4 sheet.
The assessment of the homework can also be made through a discussion with the students (from 0 to 1 value).
Students will also be asked to solve 6 exercises (open book) during practical classes, which will be corrected and assesses from 0 to 1 value.
Students can accumulate a maximum of 7 values with homework and exercises.

Special assessment (TE, DA, ...)

Final Exam

Classification improvement

An exam

Observations

Homework gives students a chance to practice their skills on modeling and analysis discussed in this course. Besides, students will get a feedback on their skills and knowledge on techniques and algorithms.
Homework has to be done individually. However, students can exchange ideas between themselves, but cannot copy colleagues’ exercises.
All exercises have to be delivered to professors’ mailbox before the deadline. Exercises deliver after the deadline will not be corrected