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Presentation
Presentation
Liner and nonlinear programming. Network optimization.
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Class from course
Class from course
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Degree | Semesters | ECTS
Degree | Semesters | ECTS
Doctorate | Semestral | 5
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Year | Nature | Language
Year | Nature | Language
1 | Optional | Português
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Code
Code
ULHT1504-25022
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Prerequisites and corequisites
Prerequisites and corequisites
Not applicable
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Professional Internship
Professional Internship
Não
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Syllabus
Syllabus
1. Linear programming 1.1 Optimization and linear programming 1.2 The graphical method 1.3 The simplex algorithm 1.4 The two-phase simplex method 2. Optimization problems for networks 2.1 The transportation problem 2.2 The minimal spanning tree 2.3 The shortest path problem 2.4 The maximum flow problem 3. Nonlinear programming (NLP) 3.1 Types of NLP problems 3.2 Convex and concave functions 3.3 Separable programming 3.4 Linear approximations of NLP problems 3.5 Method of gradient descent and the Newton method
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Objectives
Objectives
Large networks are an essential part of modern technology, and optimization of certain tasks performed by such networks is an important problem. In this course we will present some basic mathematical methods of optimization for networks and other complex systems. The students will learn some basic methods of linear and non-linear programming which can be used for task optimization for large networks and other complex systems, as well as some basic graph search algorithms.
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Teaching methodologies and assessment
Teaching methodologies and assessment
Utilization of graphs and videos from Wikipedia and YouTube.
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References
References
- Introduction to Operations Research, J. Stacho, Columbia University, New York (2014) - Linear and Nonlinear Programming, D.G. Luenberger and Y. Ye, Springer (2008)
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Office Hours
Office Hours
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Mobility
Mobility
No
