Quantitative Methods for Management

Code:

EIG0038

Acronym:

MQAD

Keywords
Classification	Keyword
OFICIAL	Quantitative Methods

Instance: 2008/2009 - 1S

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

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MIEIG	34	Syllabus since 2006/2007	5	-	7	56	187

Teaching language

Portuguese

Objectives

The managers of every company – from the private or public sectors – have to make decisions on how to allocate the organization resources. Being part of the necessary information to take decisions quantitative, the managers of today’s world must be able to assess, analyse and use it.

The aim of this course is to provide the students the suitable analytical skills and data treatment tools and quantitative models to support decision making procedures.

Program

1ª part: Forecasting Methods
FORECASTING and DECISIONS MAKING : Role of the FM in decision processes. Classification of the FM. Quantitative Methods: methods based on time series and causal methods. Underlying hypotheses and conditions of applicability. FM Selection. ANALYSIS OF DATA: How to present data. How to detect and handle exceptional data points. Advantages and risks of the aggregation of data.
ANALYSIS OF TIME SERIES: Introduction. Regression (revision of concepts studied in Statistics). Classical decomposition. Exponential Smoothing Methods


2ª part: Overview of models, applications and solution techniques of Combinatorial Optimization; Comparison between exact and approximate methods; algorithms performance; constructive and improvement heuristics. Metaheuristics: introduction; examples of population-based metaheuristics and neighborhood based.


3ª part: Management Science: analysis of quantitative models and theoretical tools that support the best management practice of operations in state-of-the art companies through a list of papers published in international Journals (ex. pricing strategies in airline and retail industries)

Mandatory literature

Joseph F. Hair, Bill Black, Barry Babin, Rolph E. Anderson, Ronald L. Tatham; Multivariate Data Analysis (6th Edition), Prentice Hall; 6 edition (October 28, 2005), 2005. ISBN: 0130329290
Burke, Edmund K. 340; Search Methodologies. ISBN: 978-0387-23460-1
Reeves, Colin R. 340; Modern heuristic techniques for combinatorial problems. ISBN: 0-07-709239-2
Makridakis, Spyros; Forecasting methods for management. ISBN: 0-471-60063-6

Teaching methods and learning activities

Practical classes: problem solving (based on worksheets) .
Theoretical classes: Presentation sessions and case studies discussion.

1st part: group of students have to analyse a case study on Forecasting Methods and produce and present a report.

2nd part: students must develop and implement a heuristic procedure to solve real-world applications and write a small report

3rd part. Analysis of scientific papers.


Active learning is motivated throughout the course.

keywords

Technological sciences

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Description	Type	Time (hours)	Weight (%)	End date
Subject Classes	Participação presencial	56,00
Assignments	Trabalho escrito	122,00
	Exame	11,00
	Total:	-	0,00

Calculation formula of final grade

Final grade is a weighted average of the individual marks obtained in the FM case study (0.20), individual test (0.25), development of the algorithm and respective report (0.30) and scientific paper analyses (0.25).