期刊
APPLIED SOFT COMPUTING
卷 107, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.asoc.2021.107327
关键词
Balancedness; Nonlinearity; Landscape analysis; Local optima networks
资金
- Australian Research Council [DE160100850, DP200102364, DP210102670]
- COST (European Cooperation in Science and Technology) [CA15140]
- Australian Research Council [DP200102364, DE160100850] Funding Source: Australian Research Council
Boolean functions have various applications in different fields, and heuristics play a vital role in their construction. This research investigates the influence of different optimization criteria and variation operators through fitness landscape analysis and Local Optima Networks, observing correlations between local optima fitness, interconnection degree, and basin sizes.
Boolean functions have numerous applications in domains as diverse as coding theory, cryptography, and telecommunications. Heuristics play an important role in the construction of Boolean functions with the desired properties for a specific purpose. However, there are only sparse results trying to understand the problem's difficulty. With this work, we aim to address this issue. We conduct a fitness landscape analysis based on Local Optima Networks (LONs) and investigate the influence of different optimization criteria and variation operators. We observe that the naive fitness formulation results in the largest networks of local optima with disconnected components. Also, the combination of variation operators can both increase or decrease the network size. Most importantly, we observe correlations of local optima's fitness, their degrees of interconnection, and the sizes of the respective basins of attraction. This can be exploited to restart algorithms dynamically and influence the degree of perturbation of the current best solution when restarting. (C) 2021 Elsevier B.V. All rights reserved.
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