Classical ELA Features

The term Exploratory Landscape Analysis (ELA) features (as introduced by Mersmann et al., 2011) summarizes a group of characteristics, which quantifies certain properties of a continuous optimization problem. In its original version, ELA covered a total of 50 features - grouped into six so-called low-level properties (Convexity, Curvature, y-Distribution, Levelset, Local Search and Meta Model). These (numerical values) were used to characterize (usually categorical and expert-designed) high-level properties, such as the Global Structure, Multimodality or Variable Scaling. The figure below visualizes the connections between the low- and high-level properties.

(Inspired by Mersmann et al., 2011)

A detailed description of the features can be found in Mersmann et al. (2011).

Literature Reference

Mersmann et al. (2011), “Exploratory Landscape Analysis”, in Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation, pp. 829—836. ACM (http://dx.doi.org/10.1145/2001576.2001690).