Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Randomized algorithms
A computational view of population genetics
STOC '95 Proceedings of the twenty-seventh annual ACM symposium on Theory of computing
On the analysis of the (1+ 1) evolutionary algorithm
Theoretical Computer Science
Evolutionary Optimization in Dynamic Environments
Evolutionary Optimization in Dynamic Environments
On the Analysis of Evolutionary Algorithms - A Proof That Crossover Really Can Help
ESA '99 Proceedings of the 7th Annual European Symposium on Algorithms
Analysis of the (1+1) EA for a dynamically bitwise changing ONEMAX
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Theoretical analysis of simple evolution strategies in quickly changing environments
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Analysis of the (1+1) EA for a dynamically bitwise changing ONEMAX
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
An analysis of the XOR dynamic problem generator based on the dynamical system
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
Perspectives in dynamic optimization evolutionary algorithm
ISICA'10 Proceedings of the 5th international conference on Advances in computation and intelligence
The use of tail inequalities on the probable computational time of randomized search heuristics
Theoretical Computer Science
ACO beats EA on a dynamic pseudo-boolean function
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part I
Tracking property of UMDA in dynamic environment by landscape framework
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Runtime analysis of ant colony optimization on dynamic shortest path problems
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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Although evolutionary algorithms (EAs) are often successfully used for the optimization of dynamically changing objective function, there are only very few theoretical results for EAs in this scenario. In this paper we analyze the (1+1) EA for a dynamically changing ONEMAX, whose target bit string changes bitwise, i. e. possibly by more than one bit in a step. We compute the movement rate of the target bit string resulting in a polynomial expected first hitting time of the (1+1) EA asymptotically exactly. This strengthens a previous result, where the dynamically changing OneMax changed only at most one bit at a time.