Fitness Landscapes Based on Sorting and Shortest Paths Problems
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Real royal road functions for constant population size
Theoretical Computer Science
On the Choice of the Offspring Population Size in Evolutionary Algorithms
Evolutionary Computation
Runtime Analysis of the (μ+1) EA on Simple Pseudo-Boolean Functions
Evolutionary Computation
On the local performance of simulated annealing and the (1+1) evolutionary algorithm
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Do additional objectives make a problem harder?
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Approximating covering problems by randomized search heuristics using multi-objective models
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Rigorous analyses of simple diversity mechanisms
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Theoretical Computer Science
Speeding up evolutionary algorithms through asymmetric mutation operators
Evolutionary Computation
Expected runtimes of evolutionary algorithms for the Eulerian cycle problem
Computers and Operations Research
Computing minimum cuts by randomized search heuristics
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Theoretical analysis of diversity mechanisms for global exploration
Proceedings of the 10th annual conference on Genetic and evolutionary computation
On the choice of the parent population size*
Evolutionary Computation
Crossover Can Be Constructive When Computing Unique Input Output Sequences
SEAL '08 Proceedings of the 7th International Conference on Simulated Evolution and Learning
Single- and multi-objective evolutionary algorithms for graph bisectioning
Proceedings of the tenth ACM SIGEVO workshop on Foundations of genetic algorithms
Additive approximations of pareto-optimal sets by evolutionary multi-objective algorithms
Proceedings of the tenth ACM SIGEVO workshop on Foundations of genetic algorithms
Comparison of simple diversity mechanisms on plateau functions
Theoretical Computer Science
Dynamic evolutionary optimisation: an analysis of frequency and magnitude of change
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Comparing Different Aging Operators
ICARIS '09 Proceedings of the 8th International Conference on Artificial Immune Systems
On the effects of adding objectives to plateau functions
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Analysis of diversity-preserving mechanisms for global exploration*
Evolutionary Computation
Analysis of the (1 + 1)-EA for finding approximate solutions to vertex cover problems
IEEE Transactions on Evolutionary Computation
Analysis of an asymmetric mutation operator
Evolutionary Computation
When to use bit-wise neutrality
Natural Computing: an international journal
Real royal road functions for constant population size
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
On the brittleness of evolutionary algorithms
FOGA'07 Proceedings of the 9th international conference on Foundations of genetic algorithms
Comparing variants of MMAS ACO algorithms on pseudo-boolean functions
SLS'07 Proceedings of the 2007 international conference on Engineering stochastic local search algorithms: designing, implementing and analyzing effective heuristics
On potential energy models for ea-based ab initio protein structure prediction
Evolutionary Computation
Analysis of computational time of simple estimation of distribution algorithms
IEEE Transactions on Evolutionary Computation
Ant colony optimization and the minimum cut problem
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Optimal fixed and adaptive mutation rates for the leadingones problem
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
More effective crossover operators for the all-pairs shortest path problem
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
On benefits and drawbacks of aging strategies for randomized search heuristics
Theoretical Computer Science
Approximating covering problems by randomized search heuristics using multi-objective models*
Evolutionary Computation
Illustration of fairness in evolutionary multi-objective optimization
Theoretical Computer Science
Proceedings of the 11th workshop proceedings on Foundations of genetic algorithms
Simple max-min ant systems and the optimization of linear pseudo-boolean functions
Proceedings of the 11th workshop proceedings on Foundations of genetic algorithms
Analysis of (1+1) evolutionary algorithm and randomized local search with memory
Evolutionary Computation
Finding mount everest and handling voids
Evolutionary Computation
Collisions are helpful for computing unique input-output sequences
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Speeding up evolutionary algorithms through restricted mutation operators
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Accessibility and runtime between convex neutral networks
SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
Proceedings of the 14th annual conference on Genetic and evolutionary computation
A Best Fit Relocation Approach for Heterogeneous Sensor Networks
Wireless Personal Communications: An International Journal
Convergence of set-based multi-objective optimization, indicators and deteriorative cycles
Theoretical Computer Science
More effective crossover operators for the all-pairs shortest path problem
Theoretical Computer Science
A runtime analysis of simple hyper-heuristics: to mix or not to mix operators
Proceedings of the twelfth workshop on Foundations of genetic algorithms XII
Runtime analysis of evolutionary algorithms: basic introduction
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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The most simple evolutionary algorithm (EA), the so-called (1 + 1) EA, accepts an offspring if its fitness is at least as large (in the case of maximization) as the fitness of its parent. The variant (1 + 1)* EA only accepts an offspring if its fitness is strictly larger than the fitness of its parent. Here, two functions related to the class of long-path functions are presented such that the (1 + 1) EA maximizes one in polynomial time and needs exponential time for the other while the (1 + 1)* EA has the opposite behavior. These results demonstrate that small changes of an EA may change its behavior significantly. Since the (1 + 1) EA and the (1 + 1)* EA differ only on plateaus of constant fitness, the results also show how EAs behave on such plateaus. The (1 + 1) EA can pass a path of constant fitness and polynomial length in polynomial time. Finally, for these functions, it is shown that local performance measures like the quality gain and the progress rate do not describe the global behavior of EAs