On the structure of multiobjective combinatorial search space: MNK‐landscapes with correlated objectives

On the structure of multiobjective combinatorial search space: MNK‐landscapes with correlated objectives

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Article ID: iaor20131654
Volume: 227
Issue: 2
Start Page Number: 331
End Page Number: 342
Publication Date: Jun 2013
Journal: European Journal of Operational Research
Authors: , , ,
Keywords: heuristics: local search
Abstract:

The structure of the search space explains the behavior of multiobjective search algorithms, and helps to design well‐performing approaches. In this work, we analyze the properties of multiobjective combinatorial search spaces, and we pay a particular attention to the correlation between the objective functions. To do so, we extend the multiobjective NK‐landscapes in order to take the objective correlation into account. We study the co‐influence of the problem dimension, the degree of non‐linearity, the number of objectives, and the objective correlation on the structure of the Pareto optimal set, in terms of cardinality and number of supported solutions, as well as on the number of Pareto local optima. This work concludes with guidelines for the design of multiobjective local search algorithms, based on the main fitness landscape features.

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