Operational Research

Code:

L.EMAT029

Acronym:

IO

Keywords
Classification	Keyword
OFICIAL	Management

Instance: 2023/2024 - 2S

Active?	Yes
Web Page:	https://sites.google.com/view/inv-op
Responsible unit:	Department of Industrial Engineering and Management
Course/CS Responsible:	Bachelor in Materials Engineering

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
L.EMAT	41	Syllabus	3	-	6	52	162

Teaching language

Portuguese

Objectives

BACKGROUND

This course focuses on the application of analytical methods to take better decisions and provides students with tools for modelling and optimization that will be very useful in various roles in several types of organizations (industry and services).

SPECIFIC OBJECTIVES

The main objective of this course is, through the creation of models, develop skills for analysing a wide range of real situations. These competencies are based on the ability to recognize the key problem in a non-structured situation, on the ability to develop a framework for analysing and treating the problem and on the application of analytical methods for its resolution.

LEARNING OBJECTIVES

Endow the students with the skills to:

• identify and address decision problems in a structured way;


• build models of decision problems;


• identify and use analytical methods to obtain solutions for the models, that should act as a support for informed decisions;


• use spreadsheets to analyse and obtain solutions for the models;


• extract information from the models to communicate and motivate organizational changes.

Learning outcomes and competences

This course will contribute to the acquisition, by the students, of the following CDIO competencies:

1. Technical Knowledge and Reasoning

1.1. Acquire proficiency with the necessary knowledge of basic sciences and be able to use them in the formulation, discussion and resolution of problems of their area;

The contents of the course unit build on knowledge of Algebra, Mathematical Analysis and Probabilities and Statistics, organizing them, developing them and applying them in a context of decision support. By nature this knowledge is transversal to all areas of Engineering and belongs to its basic sciences. Throughout the classes there is a concern to use examples and case studies from the scientific area of each course, bridging the gap between the basic sciences and area of the degree.

The assessment in the course addresses these skills.

2. Personal and Professional Skills and Attitudes
2.1. Engineering reasoning and problem solving
2.1.1 problem identification and formulation
2.1.2 modelling
2.1.3 estimation and qualitative analysis
2.1.4 analysis with uncertainty
2.1.5 solution and recommendation

Exactly these points can describe the teaching methodology and the contents of this course. Thus, the formulation of problems according to each of the models studied throughout the course, their modelling and resolution are an on-going activity. The qualitative analysis is addressed in the sensitivity analysis, while uncertainty is addressed in Queueing Theory and in Decision Theory.

The assessment in the course addresses these skills.

2.2 Experimentation and knowledge discovery
2.2.1 hypothesizing
2.2.2 literature search
2.2.3 Experimental investigation
2.2.4 test and defence of hypotheses

2.3 systemic thinking
2.3.1 holistic thinking
2.3.2 emergency and interaction between systems
2.3.3 prioritization and focus
2.3.4 trade-offs, judgment and balancing the resolution

These skills are addressed indirectly, and may be more directly described as:

(1) analysis competencies - ability to conceptualize, formulate and solve unfamiliar problems;
(2) project competencies - ability to address with creativity, unfamiliar, complex and technically uncertain problems;
(3) research competencies - ability to model and evaluate the applicability of emerging techniques (description of the criteria according to Euro-ACE).

Problem design and modelling, involving the identification of the applicable family of models and the development and evaluation of original models, clearly contributes to these skills. The topics related with sensitivity analysis contribute to the understanding of concepts related to trade-offs and balancing.

The assessment in the course addresses these skills.

The learning objectives are related to the competencies (knowledge, skills and attitudes that students should have) and are expressed as statements about things that students should be able to explain, calculate, deduct, design, etc ...

For all program topics, detailed learning objectives are available from the web site, along with educational materials to support learning.

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

Basic courses in algebra, statistics and probability theory.

Program

• modelling | without integer variables


• modelling | problems in networks


• resolution of models | without integer variables




• Excel solver


• solver sensitivity report




• modelling | with integer variables


• modelling | with integer auxiliary variables


• decision theory


• queueing theory

Mandatory literature

Docentes de IO | DEGI | FEUP; Documentação de apoio a Investigação Operacional (Available at the course site)

Complementary Bibliography

Hillier, Frederick S.; Introduction to operations research. ISBN: 0-07-118163-6
Hamdy A. Taha; Operations research. ISBN: 0-13-281172-3 (brochada)

Teaching methods and learning activities

The themes are presented using active learning methods. The problems are illustrated with examples. The problems from a list of proposed problems are discussed and solved by the students.

Software

Excel Solver

keywords

Social sciences > Economics > Management studies > Industrial management
Physical sciences > Mathematics > Applied mathematics > Operations research

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Designation	Weight (%)
Teste	100,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	110,00
Frequência das aulas	52,00
Total:	162,00

Eligibility for exams

See FEUP's general evaluation rules.

Calculation formula of final grade

DISTRIBUTED EVALUATION

Exercises in class (closed book) (0 to 10 points)
Sum of the top exercises of each student out of the exercises proposed in the end of each class, excluding the two worst classifications.
Each exercise will be rated on a scale from 0 to 100%.

2 tests (open book) (0 to 10 points).

 

Examinations or Special Assignments

Students enrolled in ORDINARY REGIME

Must make an exercise (closed book) at the end of each class.
The 11 exercises will be corrected and graded on a scale from 0 to 100%.
The results will be discussed with the students.

Must make two tests (closed book), that will be corrected and graded, in total, from 0 to 10.
The results will be discussed with the students.

Students who have no obligation to attend classes and that did not make the exercises and the tests will make a closed book examination.

Special assessment (TE, DA, ...)

These exams will be closed book.

Classification improvement

Students may improve their marks in each one of the evaluation components:

1. The component of the exercises will be assessed through a closed-book exam (rating 0 to 10 points).


2. The component of the test will be assessed through a closed-book exam (rating 0 to 10 points).

In all cases, the final classification will be calculated as explained in section "Final Classification", considering the best evaluation obtained by the student in each component.

The same rules apply to students that attend this exams for passing the course.