How to detect all maxima of a function
Theoretical aspects of evolutionary computing
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Non-parametric Estimation of Properties of Combinatorial Landscapes
Proceedings of the Applications of Evolutionary Computing on EvoWorkshops 2002: EvoCOP, EvoIASP, EvoSTIM/EvoPLAN
Fitness Landscapes and Evolutionary Algorithms
AE '99 Selected Papers from the 4th European Conference on Artificial Evolution
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Simulated annealing applied to test generation: landscape characterization and stopping criteria
Empirical Software Engineering
Multiobjective Optimization
Pareto local optima of multiobjective NK-landscapes with correlated objectives
EvoCOP'11 Proceedings of the 11th European conference on Evolutionary computation in combinatorial optimization
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The number of local optima is an important indicator of optimization problem difficulty for local search algorithms. Here we will discuss some methods of finding the confidence intervals for this parameter in problems where the large cardinality of the search space does not allow exhaustive investigation of solutions. First results are reported that were obtained by using these methods for NK landscapes, and for the low autocorrelation binary sequence and vertex cover problems.