Advanced fitness landscape analysis and the performance of memetic algorithms
Evolutionary Computation - Special issue on magnetic algorithms
Multiobjective Landscape Analysis and the Generalized Assignment Problem
Learning and Intelligent Optimization
Plateau connection structure and multiobjective metaheuristic performance
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
On confidence intervals for the number of local optima
EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing
Advances in Multi-Objective Nature Inspired Computing
Advances in Multi-Objective Nature Inspired Computing
Analyzing the effect of objective correlation on the efficient set of MNK-Landscapes
LION'05 Proceedings of the 5th international conference on Learning and Intelligent Optimization
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In this paper, we conduct a fitness landscape analysis for multiobjective combinatorial optimization, based on the local optima of multiobjective NK-landscapes with objective correlation. In singleobjective optimization, it has become clear that local optima have a strong impact on the performance of metaheuristics. Here, we propose an extension to the multiobjective case, based on the Pareto dominance. We study the co-influence of the problem dimension, the degree of nonlinearity, the number of objectives and the correlation degree between objective functions on the number of Pareto local optima.