HeuristicLab 3.3: A unified approach to metaheuristic optimization
S. Wagner, A. Beham, G. K. Kronberger, M. Kommenda, E. Pitzer, M. Kofler, S. Vonolfen, S. M. Winkler, V. Dorfer, M. Affenzeller - HeuristicLab 3.3: A unified approach to metaheuristic optimization - Actas del séptimo congreso español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB'2010), Valencia, Spain, Spanien, 2010, pp. 8
The awareness of heuristic methods as optimization tools and their, in comparison to exact algorithms, quick and simple application has expanded to many different domains in the recent history. In the course of these developments the user base of heuristic optimization methods has also grown from mathematicians and computer scientists to practitioners in virtually every field. To facilitate the application of heuristic optimizers in domains where no computer-scientist has gone before, a number of more or less advanced software frameworks exists. In this paper the authors introduce a new version of their software environment HeuristicLab which aims to provide a comprehensive solution for algorithm development, testing, analysis and generally the optimization of complex problems.