Heuristic search algorithms have been successfully applied to solve many problems in practice. Their design, however, has increased in complexity as the number of parameters and choices for operators and algorithmic components is also expanding. There is clearly the need for providing the final user with automated tools to assist the tuning, design and assessment of heuristic optimisation methods. In recent years a growing number workshops and tracks has been held to address these issues. In 2010, the Parallel Problem Solving from Nature (PPSN) conference hosted two workshops, which decided to joint efforts to organise this journal special issue. The workshop “Self-Tuning, Self-Configuring and Self-Generating Search Heuristics,” distinguished three general processes in automated heuristic design: 1) tuning: the process of adjusting the algorithm's control parameters, 2) configuring: the process of selecting and using existing algorithmic components such as search operators, construction...
Editorial for the Special Issue on Automated Design and Assessment of Heuristic Search Methods
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Gabriela Ochoa, Mike Preuss, Thomas Bartz-Beielstein, Marc Schoenauer; Editorial for the Special Issue on Automated Design and Assessment of Heuristic Search Methods. Evol Comput 2012; 20 (2): 161–163. doi: https://doi.org/10.1162/EVCO_e_00071
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