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Optimização e Decisão

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6 ECTSP3Exam: Mandatory
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Description

Objectives

The main objective of this discipline is to supply the students with the basics of optimization and decision theory. The students must learn how to formulate typical optimization problems. Beyond the traditional techniques, meta-heuristics will also be addressed, including the most recent meta- heuristics inspired in biologic agents.

Syllabus

Introduction to optimization problems in Engineering. Modeling optimization problems. Linear Programming: simplex, duality theory and sensitivity analysis. The transportation and assignment problems. Network optimization models. Deterministic and probabilistic dynamic programming. Integer programming. Binary integer programming. Branch-and-bound algorithms for integer programming and mixed integer programming (MIP). Nonlinear programming. Types of nonlinear programming problems. The Karush-Kuhn-Tucker (KKT) conditions for constrained optimization. Quadratic Programming. Convex and non-convex programming. Metaheuristics. Tabu search. Simulated annealing. Genetic algorithms. Ant colony optimization. Particle Swarm Optimization. Application to the traveling salesman problem, knapsack problems and others. Decision analysis. Decision making with and without experimentation. Decision trees. Utility theory. Practical application of decision analysis.

Cross Competence Component

Project done in group requires critical and inovative reasoning, decision making, team work, leadership, oral communication skills, use of computer multimedia tools (20% of the evaluation component of the project).

Laboratorial Component

Development of software for solving optimization problems using metaheuristics.

Programming And Computing Component

Use of several software tools for optimization.

Ethical Principles

All members of a group are responsible for the group’s work In any assessment, every student shall honestly disclose any help received and sources used. In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.