Our overall objective is to make modern and efficient methods for solving hard optimization problems accessible to a wide range of users, including non-experts. We plan to achieve this objective by further developing the software tool SCIL, which has already been used successfully in many different applied projects. The first step is to extend its flexibility and user-friendliness significantly. The second step is to improve and extend the internal methods of SCIL in order to increase performance and guarantee exactness. At the same time, we plan to evaluate the progress by applying SCIL and its new features to various applications from different areas such as network design and production planning.
Combining research on general methods with the immediate application to practical optimization problems has many advantages: on the one hand, this ensures that the implementation process is guided by practical considerations right from the start. Focusing on specific applications allows to evaluate these methods by extensive computational experiments. Conversely, the examination of particular applications will hopefully stimulate research on new methods and give ideas for further improvements of SCIL that apply to more general problem types. In other words, the simultaneous consideration of general methods and specific applications in one project leads to a software development in the spirit of Algorithm Engineering.