
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.
This lecture gives you a problem solving skill to deal with force, energy, and equilibrium problems.
In this lecture you will be able to write an optimization code in GAMS to solve an energy, force, and equilibrium problem and to find the optimized result for the problem discussed in the previous lecture.
This lecture describes the main concepts in Dynamics problems including dynamics, mathematical modelling, simulation, and control engineering.
This lecture describes the main concepts in Dynamics problems including dynamics, mathematical modelling, simulation, and control engineering.
In this lecture, an interesting real-world example on position control of a spacecraft is discussed.
Before you start this module please have quick look at this video
How to install GAMS ?
you will learn how to define a mixed-integer linear problem as an optimization problem in GAMS.
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.
In a given sphere find a cylinder of maximal volume
(Steiner) In the plane of a triangle, find a point such that the sum of its distances to the vertices of the triangle is minimal.
A and B are two given points on the same side of a line ℓ. Find a point D on ℓ such that the sum of the distances form A to D and from D to B is a minimum.
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.