Operations Research (OR) is a field in which people use mathematical and engineering methods to study optimization problems in Business and Management, Economics, Computer Science, Civil Engineering, Electrical Engineering, etc.
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Operations Research (2): Optimization Algorithms
Universidad Nacional de TaiwánAcerca de este Curso
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Certificado para compartir
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100 % en línea
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Nivel intermedio
For learners who have already taken basic operations research courses. Experience with calculus, linear algebra, and probability is suggested.
Aprox. 12 horas para completar
Inglés (English)
Subtítulos: Inglés (English)
Qué aprenderás
Learn how to use algorithms to solve different types of optimization programs.
Learn how to use Gurobi solver with Python to solve these problems efficiently.
Habilidades que obtendrás
- Algorithms
- Business Analytics
- Mathematical Optimization
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Nivel intermedio
For learners who have already taken basic operations research courses. Experience with calculus, linear algebra, and probability is suggested.
Aprox. 12 horas para completar
Inglés (English)
Subtítulos: Inglés (English)
ofrecido por
Universidad Nacional de Taiwán
We firmly believe that open access to learning is a powerful socioeconomic equalizer. NTU is especially delighted to join other world-class universities on Coursera and to offer quality university courses to the Chinese-speaking population. We hope to transform the rich rewards of learning from a limited commodity to an experience available to all.
Programa - Qué aprenderás en este curso
2 horas para completar
Course Overview
In the first lecture, we briefly introduce the course and give a quick review about some basic knowledge of linear algebra, including Gaussian elimination, Gauss-Jordan elimination, and definition of linear independence.
2 horas para completar
7 videos (Total 73 minutos), 1 lectura, 1 cuestionario
3 horas para completar
The Simplex Method
Complicated linear programs were difficult to solve until Dr. George Dantzig developed the simplex method. In this week, we first introduce the standard form and the basic solutions of a linear program. With the above ideas, we focus on the simplex method and study how it efficiently solves a linear program. Finally, we discuss some properties of unbounded and infeasible problems, which can help us identify whether a problem has optimal solution.
3 horas para completar
25 videos (Total 168 minutos)
2 horas para completar
The Branch-and-Bound Algorithm
Integer programming is a special case of linear programming, with some of the variables must only take integer values. In this week, we introduce the concept of linear relaxation and the Branch-and-Bound algorithm for solving integer programs.
2 horas para completar
16 videos (Total 121 minutos)
2 horas para completar
Gradient Descent and Newton’s Method
In the past two weeks, we discuss the algorithms of solving linear and integer programs, while now we focus on nonlinear programs. In this week, we first review some necessary knowledge such as gradients and Hessians. Second, we introduce gradient descent and Newton’s method to solve nonlinear programs. We also compare these two methods in the end of the lesson.
2 horas para completar
13 videos (Total 102 minutos)
Reseñas
- 5 stars89,13 %
- 4 stars6,52 %
- 2 stars2,17 %
- 1 star2,17 %
Principales reseñas sobre OPERATIONS RESEARCH (2): OPTIMIZATION ALGORITHMS
por HP15 de sep. de 2021
The Course was done earlier, hence, there was no one to answer the forums or questions, otherwise a very good course to learn about applying Python.
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