In design and development of technical products, there are frequently design problems with many evaluation criteria as low cost, low noises, high accuracy etc. Design parameters have to be found to satisfy all criteria. In contrast to a single optimization, there is another order structure between parameter space and design spaces at a multi-objective optimization. Criteria conflict each other. Trying to minimize a criterion, other criteria may be maximized. There is not only one solution, but also a Pareto solution frontier. Multi-objective optimization can automatically find all Pareto solutions with a single run.
Decision Making Support
For technical product, only one solution from the optimal Pareto set is needed. The decision making is very difficult. There are no exactly comparing criteria between the alternative designs. A mathematical decision making support tool is available. The choice of a best suitable solution is done automatically by input of an ideal and normalized design point by user.