The rate of convergence to optimality of the LPT rule
Discrete Applied Mathematics
Discrete Applied Mathematics
Computers and Intractability; A Guide to the Theory of NP-Completeness
Computers and Intractability; A Guide to the Theory of NP-Completeness
Algorithmics for Hard Problems
Algorithmics for Hard Problems
Upper and Lower Bounds for Randomized Search Heuristics in Black-Box Optimization
Theory of Computing Systems
Black-box search by elimination of fitness functions
Proceedings of the tenth ACM SIGEVO workshop on Foundations of genetic algorithms
Black-box search by unbiased variation
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Faster black-box algorithms through higher arity operators
Proceedings of the 11th workshop proceedings on Foundations of genetic algorithms
Theory of Randomized Search Heuristics: Foundations and Recent Developments
Theory of Randomized Search Heuristics: Foundations and Recent Developments
Black-box complexities of combinatorial problems
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Towards a complexity theory of randomized search heuristics: ranking-based black-box complexity
CSR'11 Proceedings of the 6th international conference on Computer science: theory and applications
Worst-case and average-case approximations by simple randomized search heuristics
STACS'05 Proceedings of the 22nd annual conference on Theoretical Aspects of Computer Science
Black-box complexities of combinatorial problems
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Black-box complexities of combinatorial problems
Theoretical Computer Science
Black-box complexity: from complexity theory to playing mastermind
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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Unbiased black-box complexity was recently introduced as a refined complexity model for randomized search heuristics (Lehre and Witt, GECCO 2010). For several problems, this notion avoids the unrealistically low complexity results given by the classical model of Droste, Jansen, and Wegener (Theor. Comput. Sci. 2006). In this work, we show that for two natural problems the unbiased black-box complexity remains artificially small. For the classical JumpK test function class and for a subclass of the well-known Partition problem, we give mutation-only unbiased black-box algorithms having complexity O(n log n). Since the first problem usually needs Theta(nk) function evaluations to be optimized by standard heuristics and the second is even NP-complete, these black-box complexities seem not to indicate the true difficulty of the two problems for randomized search heuristics.