Simplifying Problem Definitions in the HeuristicLab Optimization Environment
A. Scheibenpflug, A. Beham, M. Kommenda, J. Karder, S. Wagner, M. Affenzeller - Simplifying Problem Definitions in the HeuristicLab Optimization Environment - Companion Publication of the 2015 Genetic and Evolutionary Computation Conference, GECCO'15 Companion, Madrid, Spain, 2015, pp. 1101-1108
Software frameworks for metaheuristic optimization take the burden off researchers and practitioners to start from scratch and implement their own algorithms and problems. One such framework is HeuristicLab. While it allows using existing, already implemented algorithms and problems comfortably and provides an extensive range of tools for analyzing results, it lacks an easy to use programming interface for adding new problems. As implementing new problems is a common task, an improved and simpler problem definition interface has been created. Besides giving an overview of the implementation, we also show examples of problems built using this new interface. Additionally, we compare the new approach to three other metaheuristic frameworks. This is done by analyzing the source code of the OneMax problem implemented in each framework and comparing the resulting lines of code with previous works.