Step by Step Optimization problems in Mechanical Engineering
- 3 hours on-demand video
- 11 downloadable resources
- Full lifetime access
- Access on mobile and TV
- Certificate of Completion
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Try Udemy for Business- How to apply Optimization Algorithms in Real-World Mechanical Engineering Problems
- Students should have preliminary knowledge about mathematics, physics, and preferably mechanical engineering
This course presents a methodological and systematic set of guidelines and applications of optimization algorithms (e.g. GAMS) for real-world problems in mechanical engineering.
It provides an invaluable resource for undergraduate/postgraduate students as well as practicing engineers working in the mechanical engineering sector
It contains several applied case-studies, industrial and practical examples.
In this course, you will learn:
The basics of optimization techniques applied to mechanical engineering problems.
The problem-solving skill that enables you to deal with the practical aspects of optimization and mechanical engineering.
How to formulate a real-world mechanical engineering problem as an engineering optimization problem.
How to write optimization codes for applying on mechanical engineering problems.
How to deal with real problems from industry and the approach that should be taken to solve them.
- undergraduate/postgraduate students as well as practicing engineers working in mechanical engineering sector
This course will focus on formulation of real-world statics problem in the form of engineering optimization problems and to provide a methodological approach to deal with these problems in a smart, practical way.
This lecture gives an introduction and overview of the whole course to help students to familiar themselves with the road map of the course.
This lecture gives you an interesting graphical idea about the force, energy, equilibrium and the relation between these concepts.
Quadratic programming (QP) is the process of solving a special type of mathematical optimization problem—specifically, a (linearly constrained) quadratic optimization problem, that is, the problem of optimizing (minimizing or maximizing) a quadratic function of several variables subject to linear constraints on these variables. Quadratic programming is a particular type of nonlinear programming.