Discrete optimisation and real-world problems

In the global economy, proper organisation and planning of production and storage locations, transportation and scheduling are vital to retain the competitive edge of companies. The planning and scheduling problems involved are immensely complex. Computer-based optimisation techniques are the best means of obtaining viable solutions, but until now the mixed integer programs developed have been able to deal only with simple problems. The more important larger problems have generally been solved using ad-hoc heuristics which often produce incomplete and less satisfactory solutions. Today, the development of new algorithms, software and hardware is leading to the provision of mathematical applications and tools which allow the solution of these larger problems in acceptable times. In this contribution two groups are addressed: on the one hand managers, and on the other hand a more technical oriented audience. The focus towards the first group is to create some attention with respect to the potential benefits of the method, to transmit a sense of what kind of problems can be tackled, and to increase the acceptance of the approach based on mixed-integer optimisation. The second group will be informed about the state-of-the-art, especially with respect to the use of high-performance computers and modern algorithmic aspects.