A relevant undergraduate bachelor Engineering programme with minimum 30 credits Mathematics/statistics topics.
Prerequisite(s) Knowledge about linear algebra, classical calculus (maximum/minimum for multi-variable functions) and computer programming at bachelor level.
Application code: 9371
Linear optimization concerns the application of mathematical modelling of complex linear problems arising in management and operation of complex systems, consisting of human beings, machines, materials and capital. The purpose is to help management people and problem solvers to determine its policy and actions by allocation of resources. Considered techniques are: Linear programming, integer programming, network analysis, and transportation problems. Applications: Production planning, product-mix decision making, routing and scheduling of vehicles and crews, blending problems. Furthermore, the historical development, the practical significance and the limitations of the linear mathematical modelling are being discussed.
Industrial Technology Nonlinear Optimisation:
Nonlinear optimisation considers problems to find best (in a well-defined sense) solutions with in general nonlinear problems. Selected topics are the application of nonlinear optimisation in Industrial Technology, solution of nonlinear optimisation problems with both discrete and continuous variables, special optimisation problems, graphical optimisation, software tools for nonlinear optimisation, use of experience-based systems, systems analysis via nonlinear optimisation, optimization algorithms and heuristics methods.
Objectives of the course
The course give and introduction to operations research and provides the student knowledge of mathematical modelling of complex linear and nonlinear industrial problems and different basic optimization techniques connected to these models.
The candidate will be able to, from a text based description, set up linear and nonlinear
models to optimize industrial problems.
The candidate will have the ability to use different basic optimisation techniques connected to linear and nonlinear models.
The candidate will have the ability to use different software as tools for optimisation of linear and nonlinear models.
General (overall) Qualifications: Based on the given knowledge and skills in mathematical modelling of linear and nonlinear problems the candidate shall be able to communicate, solve and improve related problems in future education and working life.
Linear optimisation: There are five compulsory exercises.
Industrial Technology Nonlinear Optimisation: There are five compulsory exercises.
Examination and assessment
3 hour written individual examination under supervision.
Grading will be done by using A-F grading scale, where F is a fail.
The grade will be based solely om the result of the examination.
A re-sit exam will be arranged for this course.