| Code |
15418
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| Year |
1
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| Semester |
S2
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| ECTS Credits |
6
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| Workload |
T(30H)/TP(30H)
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| Scientific area |
Engenharia e Gestão Industrial
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Entry requirements |
Not applicable.
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Mode of delivery |
Face-to-face
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Learning outcomes |
Show the potential of decision support methods in the context of Control, Operations Research, Management and Artificial Intelligence, with particular emphasis on the formulation of decision problems in Engineering and particularly useful tools to optimize solutions.
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Syllabus |
1. Linear programming.
1.1 Graphic method.
1.2 Simplex Algorithm.
1.3 Sensitivity Analysis.
1.4 Particular cases of linear programming.
2. Optimization on networks and graphs.
2.1 Graph theory.
2.2 Algorithms for maximum flow problems.
2.3 Algorithm for the shortest path.
2.4 Minimum Tree links.
3. Planning and scheduling.
3.1 Material Requirements Planning (MRP).
3.2 JIT Concept.
3.3 Management of projects.
3.4 Graphcal representation of projects.
3.5 Project Management with unlimited and limited resources PERT / CPM).
3.6 Sequencing of tasks.
4. Queues.
4.1 Markov Chains.
4.2 Queues M/M/1, M/M/m.
4.3 Networks of queues.
4.4 Petri Nets.
5. Digital simulation.
5.1 Simulation methods.
5.2 Methodologies for analyzing and structuring models.
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Main Bibliography |
P.A. Jensen. Operations Research Models and Methods, 1st Ed. Wiley, 2002.
F.S. Hillier, G.J. Lieberman. Introduction to Operations Research, 10th Ed. McGrawHill, 2014.
P.R. Murthy. Operations Research. New Age Int. Publishers, 2008.
D. Blumenfeld. Operations Research Calculations Handbook. CRC Press, 2009.
W.J. Stevenson. Operations management, 11th Ed. McGraw-Hill/Irwin, 2012.
J.F. Hair, B. Black, B. Babin, R.E. Anderson, R.L. Tatham; Multivariate Data Analysis (6th Edition), Prentice Hall, 2005.
E.K. Burke, G. Kendall. Search Methodologies - Introductory Tutorials in Optimization and Decision Support Techniques. Springer, 2014.
C.R. Reeves, Modern heuristic techniques for combinatorial problems, John Wiley & Sons, 1993.
S.G. Makridakis, S.C. Wheelwright, R.J. Hyndman. Forecasting: Methods and Applications, 3rd Ed., Wiley, 1998.
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Teaching Methodologies and Assessment Criteria |
Taking into account that the curricular contents have a modular character, students are evaluated in a continuous way, through an analysis and synthesis work (ASW), 3 individual practical exercises, a written knowledge assessment test, and a final project. The ASW and the final project will be performed in groups consisting of 3 elements.
Students are required to attend classes corresponding to 75% of the contact hours. The minimum approval rating is 10 (ten) values, on a scale of 0 to 20. All components present in the evaluation criteria must be performed, and each of these with approval greater than 6 values in order to be admitted to the exam. The formula for calculating the final grade is applicable in the teaching-learning period and in the exam periods. The improvement of the final classification requires the completion of a final exam.
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Language |
Portuguese. Tutorial support is available in English.
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