Guest Editorial Special Issue on Benchmarking Sampling-Based Optimization Heuristics: Methodology and Software

IEEE Transactions on Evolutionary Computation, vol. 26, pp. 1202–1205

Abstract

Benchmarking provides an essential ground base for adequately assessing and comparing evolutionary computation methods and other optimization algorithms. It allows us to gain insights into strengths and weaknesses of different existing techniques, and consequently design more efficient optimization approaches. The need for good benchmarking practices opens up a broad range of complementary research questions, arising as a byproduct of challenges encountered when optimization methods are assessed. From the selection of representative benchmark problem instances, different algorithms, and suitable performance metrics, over efficient experimentation, to a sound evaluation of the benchmark data, these research questions lie at the core of establishing a well-designed and standardized benchmarking procedure.

Authors 4

1. Thomas Bäck Aachen

   Leiden University

   Affiliation as printed

   Leiden Institute of Advanced Computer Science Leiden University, Leiden, The Netherlands

2. Carola Doerr

   Centre National de la Recherche Scientifique · LIP6

   Affiliation as printed

   Sorbonne Université CNRS, LIP6, Paris, France

3. Bernhard Sendhoff
   Affiliation as printed

   Honda Research Institute Europe, Offenbach, Germany

4. Thomas Stützle

   Université Libre de Bruxelles

   Affiliation as printed

   IRIDIA Laboratory, Université Libre de Bruxelles, Bruxelles, Belgium