All large-scale and complex operations must be planned, especiallywhere cost is a factor. In many cases, the problems are too difficultto solve for a human being. A common property for many of theseproblems is that they give large, difficult combinatorial models thatrequire research to be resolved.
We are surrounded by optimization problems all the time, but few ofthem are solved. One must see that it is an optimization problem,formulate it in mathematical detachable manner and find a suitablesolution method. This can happen in snow removal, production planning,human resource planning, or placement of unmanned aerial vehicles.
To be able to formulate a solvable but relevant model requiresexperience, and to develop an efficient solution method requires bothdeep and broad knowledge in various fields of optimization. Oftendevelopment of new methods and software is required in order to beable to solve the models. In addition, a thorough knowledge of theoriginal problem is essential, so our work is based on a high degreeof cooperation. Our main expertise lies in formulating and solvingreal optimization problems that has not been solved before.
Applications in Optimization
Optimization can be used in many diverse areas. Examples of what wehave in recent years been working on are (large and small):
- Optimal digital map matching.
- Optimal formation of student groups.
- Optimal snow removal.
- Optimal placement of unmanned aircraft as communications relays.
- Optimal planning of military attack patterns.
- Optimal planning of public transport with electric vehicles.
- Optimal scheduling of activities in the electronic systems of the aircraft.
Previous research has also concerned the design of bearings,radiation doses in cancer treatment, design and management of IPnetworks, planning of logging and optimized pits, and more.
