# Upper and Lower Bounds for Randomized Search Heuristics in Black-Box Optimization

@article{Droste2004UpperAL, title={Upper and Lower Bounds for Randomized Search Heuristics in Black-Box Optimization}, author={Stefan Droste and T. Jansen and Ingo Wegener}, journal={Theory of Computing Systems}, year={2004}, volume={39}, pages={525-544} }

Abstract
Randomized search heuristics like local search, tabu search, simulated
annealing, or all kinds of evolutionary algorithms have many applications. However,
for most problems the best worst-case expected run times are achieved by more
problem-specific algorithms. This raises the question about the limits of general
randomized search heuristics. Here a framework called black-box optimization is developed. The essential
issue is that the problem but not the problem instance is knownto the… Expand

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