Abstract
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 single-objective 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 non-linearity, the number of objectives and the correlation degree between objective functions on the number of Pareto local optima.
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Verel, S., Liefooghe, A., Jourdan, L., Dhaenens, C. (2011). Pareto Local Optima of Multiobjective NK-Landscapes with Correlated Objectives. In: Merz, P., Hao, JK. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2011. Lecture Notes in Computer Science, vol 6622. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20364-0_20
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DOI: https://doi.org/10.1007/978-3-642-20364-0_20
Publisher Name: Springer, Berlin, Heidelberg
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