Operational Research

Code:

L.EGI025

Acronym:

IO

Keywords
Classification	Keyword
OFICIAL	Statistic and Operational Research

Instance: 2021/2022 - 1S

Active?	Yes
Responsible unit:	Department of Industrial Engineering and Management
Course/CS Responsible:	Bachelor in Industrial Engineering and Management

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
L.EGI	81	Syllabus	3	-	6	52	162

Teaching language

Portuguese

Objectives

The main objective of this course is to give students an overview of the principles and techniques of Operational Research, highlighting in particular the role of quantitative methods in decision-making. It is also intended that students develop the skills necessary to identify situations where decision support techniques can be applied. At the end of the course students should be able to apply the techniques studied in real contexts.

Learning outcomes and competences

At the end of the course students should have acquired the following skills: (i) to identify decision problems, (ii) to apply the appropriate techniques in the various stages of analysis of decision problems, including defining and structuring the problems, building models, and using quantitative methods to obtain a solution, (iii) to review and validate the solution, (iv) to recognize the importance of promoting changes in organizations.

Working method

Presencial

Program

1. INTRODUCTION TO OPERATIONAL RESEARCH (OR): Brief historical note. Methodology of OR. Modelling skills.

2. LINEAR PROGRAMMING (LP). Problem formulation; obtaining the optional solution graphically and using computer software; sensitivity analysis; Simplex Method.
3. INTEGER PROGRAMMING. Contexts that require the integrality of the decision variables. Formulation of Integer Programming and Binary Programming problems. Examples of "Yes or No" decisions and Set Coverage Problems. Problems with Fixed Costs, "or -or" and "if-then" constraints, and compliance with a subset of constraints.

4. TRANSPORTATION AND ASSIGNMENT PROBLEMS: Formulation of problems and specific algorithms to obtain the optimal solution: Transportation algorithm and Hungarian method.

5. NETWORK OPTIMIZATION PROBLEMS. Maximum flow problems. Shortest path problems. Minimum cost flow problems. Specific algorithms for network otimization problems: maximum flow algorithm and  Dijktra algorithm.

6. MULTICRITERIA DECISION MAKING. Goal Programming.

Mandatory literature

Ana Camanho; Apontamentos da Unidade Curricular no Moodle, 2021

Complementary Bibliography

Hillier, Frederick S.; Introduction to management science. ISBN: 0-07-119554-8
Winston, Wayne L.; Operations research. ISBN: 0-534-20971-8
Hillier, Frederick S.; Introduction to operations research. ISBN: 0-07-118163-6

Comments from the literature

MAIN BIBLIOGRAPHY: Documentation prepared by the Lectures of the Course, available on Moodle. OTHER BIBLIOGRAPHY: Books in English available in the library catalog.

Teaching methods and learning activities

This course combines classes to lecture 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

IBM ILOG CPLEX Optimization Studio

keywords

Physical sciences > Mathematics > Applied mathematics > Operations research

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Designation	Weight (%)
Trabalho escrito	20,00
Teste	80,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Elaboração de projeto	30,00
Estudo autónomo	76,00
Frequência das aulas	56,00
Total:	162,00

Eligibility for exams

Students have to attend classes (according to the "General Evaluation Rules" of FEUP Pedagogical Council).

Calculation formula of final grade

The final grade will be calculated based on the result obtained in two tests (with a total weight of 80%) and the group work (20% weighting). At the time of appeal, the exam covering all topics of the course will have a weight of 80%, and the group work will have a weight of 20% (identical to the weight used for the normal evaluation period).

For all components of evaluation (testes and group work), it is required a minimum grade of 7.5 points (out of 20).

The 1st test evaluates themes 1 to 4 of the Curriculum Unit Programme (Linear Programming, Integer Programming, Transport and Assignment Problems) and has a weight of 50% in the final evaluation of the Curricular Unit.

The 2nd test evaluates themes 5 and 6 of the Curriculum Unit Programme (Network Optimization Problems and Multicriteria Decision Making) and has a weight of 30% in the final evaluation of the Curricular Unit.

Examinations or Special Assignments

Not applicable

Internship work/project

Not applicable

Special assessment (TE, DA, ...)

Students with special status (student union leaders and high-level competition athletes) can opt to be assessed as normal students, according to the rules previously described. Alternatively, they can take the final exam at the period especially designed for students with special status. In this case, the weight of the tests remains equal to 80% and the weight of the group work equal to 20%

Classification improvement

Students can take the evaluation component of the tests at the exam in the appeal period.

Students may also improve their classification in the following academic year by repeating the tests.

The classification of the work group will be considered in the case of repeating the tests to improve the classification in the appeal period, or in the following academic year.