| | 1 | <b>HeuristicLab</b> is a framework for <b>heuristic and evolutionary algorithms</b>, developed and successively applied by members of the <b>Heuristic and Evolutionary Algorithms Laboratory</b> since 2002. Among other aspects, a sophisticated graphical user interface distinguishes HeuristicLab from existing heuristic optimization frameworks, which usually require comprehensive programming skills to adjust and extend the algorithms for a particular problem. In HeuristicLab algorithms are represented as operator graphs and changing or rearranging operators can be done by drag-and-drop without actually writing code. The framework thereby shifts algorithm development capability from the software engineer to the user and practitioner. It is of course still possible to extend the framework on code level and algorithm developers benefit from HeuristicLab’s light-weight plug-in mechanism that allows them to integrate custom algorithms, solution representations or optimization problems with ease. This concept leads to a significant level of code reuse across metaheuristic variants and encourages users to successively gain more knowledge about algorithm development. |
