Course content

Applied nonlinear optimisation, definition of mathematical optimisation. Survey about treatment/solution of nonlinear optimisation problems with mainly continuous but also discrete variables, special optimisation problems, graphical optimisation, contributions to creative/innovative engineering work (e.g., Computer-Aided Engineering, - Design, - Manufacturing and - Quality Assurance), software tools for nonlinear optimisation (e.g. MS Excel Solver, MATLAB Optimization Toolbox, Pro/ENGINEER Mechanica, NOSYS, etc.), systems analysis via nonlinear optimisation, selected applications in Production and Quality Engineering and related areas, derivation of a fundament for an optimisation-based manufacturing systematics.

Learning outcome

This course provides broad and deep engineering mathematics about applied optimisation in Production and Quality Engineering. It is offered for both engineering and management staff in Production Engineering, but also for all other optimisation-interested people to make them familiar with and able to use the powerful possibilities in substantial, applied optimisation for better utilisation of resources in work force, material, energy, time, information, etc. It is being given a streamlined insight into and experiences of nonlinear optimisation modelling, the numerical treatment of such tasks and the application of optimisation software tools to solve corresponding problems in their own and many other working fields, and therefore capabilities to independent adjustment and even renewing on own initiative. It is emphasised that the participants develop an international view on their profession and capabilities to international co-operation.

Learning methods and activities

Lectures, exercises, project work with the topic in the PhD project's research area, one colloquium. The course requires an accepted project report about the treatment of an applied optimisation problem containing technical, PC and other experimental work. The project evaluation gives 50 % of the final grade in an oral examination. The course is being given in English.

Compulsory assignments

• Exercises

Recommended previous knowledge

Knowledge about classical calculus (maximum/minimum for multivariable functions), computer programming. Ideas on matters what/how to improve in the participants' PhD project working areas are advantageous.

Course materials

KOCH, W. H.: Production Engineering Nonlinear Optimisation. Lecture Notes, Trondheim, 2011.
KOCH, W. H.: On the utilisation of several optimisation software systems. Working paper, Trondheim, 2011.
KOCH, W. H.: PRODENO exercises. Working paper, NTNU Trondheim, 2011.
KOCH, W. H.: NOSYS task collection. Trondheim, 2006-2011.
Support:
NOCEDAL, J./WRIGHT, S. J.: Numerical Optimization. Second edition. Springer Series in Operations Research, New York, 2006.
VENKATARAMAN, P.: Applied Optimization with MATLAB Programming. Wiley, second edition, 2009.
Selected papers from scientific journals.

Credit reductions