Code: | EIG0038 | Acronym: | MQAD |
Keywords | |
---|---|
Classification | Keyword |
OFICIAL | Quantitative Methods |
Active? | Yes |
E-learning page: | https://moodle.fe.up.pt/ |
Responsible unit: | Department of Industrial Engineering and Management |
Course/CS Responsible: | Master in Engineering and Industrial Management |
Acronym | No. of Students | Study Plan | Curricular Years | Credits UCN | Credits ECTS | Contact hours | Total Time |
---|---|---|---|---|---|---|---|
MIEIG | 49 | Syllabus since 2006/2007 | 5 | - | 7 | 56 | 187 |
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.
Analytical skills and data treatment tools and quantitative models to support decision making procedures.
Operations Research
Statistics
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)
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.
Description | Type | Time (hours) | Weight (%) | End date |
---|---|---|---|---|
Case study and group work | Trabalho de campo | 89,00 | 65,00 | 2012-12-21 |
Individual Tests | Teste | 48,00 | 35,00 | 2012-12-14 |
Total: | - | 100,00 |
Description | Type | Time (hours) | End date |
---|---|---|---|
Classes | Frequência das aulas | 52 | 2012-12-20 |
Total: | 52,00 |
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).