= Thomas Stützle
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<Thomas Stützle> researches computational optimization, including <local search> and <algorithm configuration>. His author-maintained IRIDIA homepage describes the irace configuration software and its use of racing algorithms.<Thomas Stützle homepage>[News, irace software; General Info and Publications]{ref} He also coauthored <Iterated Local Search by Helena R. Lourenço and others> with <Helena Ramalhinho Dias Lourenço> and <Olivier C. Martin>.<Iterated Local Search by Helena R. Lourenço and others>[Title-page byline; §§2–3]{ref}
The modular <iterated local search> framework keeps the embedded <local search> distinct from a <local-search perturbation> and the subsequent acceptance decision. That separation makes a solver's settings part of the experimental description rather than incidental implementation detail.
An original budget comparison illustrates a configuration pitfall. Suppose setting A takes $1\,\mathrm{ms}$ per objective evaluation and setting B takes $2\,\mathrm{ms}$, with all other costs neglected. In a $100\,\mathrm{ms}$ budget they can perform $100$ and $50$ evaluations respectively. Comparing both after $100$ evaluations instead gives B twice as much time. Neither evaluation count nor elapsed time is inherently the wrong budget; the comparison must state which resource is constrained. These are hypothetical costs, not irace timings.
This is why <algorithm configuration> and <algorithm selection> are related but distinct: one tunes a parameterized solver, while the other chooses among candidates for an instance. A useful evaluation records the tuned parameters, computational budget and held-out instances alongside solution quality.
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