What you'll learn

Describe the optimization problem with objectives, variables and constraints

Model mathematically the optimization problem

Solve the optimization problems using graphical method

Employ Microsoft Excel to solve optimization problems

Develop methods to solve multi-objective optimization

Requirements

Anybody can study this course

Description

This course aims to teach Engineering students and professionals how to use optimization in design, planning and operation of different engineering systems. The course starts with the reasons to use optimization to how to solve optimization problem followed by how to deal with multi-objective optimization. Optimization is a widely used technique in Operational Research that has been employed in a range of applications. The aim is to maximize or minimize a function (e.g. maximizing profit or minimizing environmental impact) subject to a set of constraints. The action of making the best or most effective use of a situation or resource. The result of optimization process is an optimal solution not optimum one. Everyday you do an optimization in your daily life. It could be a process to reach maximum or minimum of something like minimum cost or error maximum profit or reserve. However, in many situations, decision makers find themselves wanting to optimize several different objective functions at the same time. This leads to Multi-Objective Optimization (MOO). It is easy to see that if the multiple objectives do not coincide, this problem becomes considerably more difficult.The course is very useful for: ±Communications system engineering±Computer systems engineering±Computer science and systems engineering±Control systems engineering±Earth systems engineering and management±Electronic systems engineering.±Enterprise systems engineering±Environmental systems engineering.±Petroleum systems engineering±Power systems engineering.±Process systems engineering

Who this course is for

Engineering students and professionals from all disciplines

Science students

Computer science students