Guest Editorial Special Issue on Benchmarking Sampling-Based Optimization Heuristics: Methodology and Software - Sorbonne Université Access content directly
Journal Articles IEEE Transactions on Evolutionary Computation Year : 2022

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

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.
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Dates and versions

hal-04180572 , version 1 (12-08-2023)

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Thomas Bäck, Carola Doerr, Bernhard Sendhoff, Thomas Stützle. Guest Editorial Special Issue on Benchmarking Sampling-Based Optimization Heuristics: Methodology and Software. IEEE Transactions on Evolutionary Computation, 2022, 26 (6), pp.1202-1205. ⟨10.1109/TEVC.2022.3223292⟩. ⟨hal-04180572⟩
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