Abstract

The results presented in this paper make up the basis for a new way of analyzing extremal problems. A new phenomenon that characterizes an extremal problem has been discovered. The paper tries to reveal fields of application of this phenomenon. The method of animated visual analysis, based on the knowledge discovery in the set of observations of the objective function of the problem interactively, has been developed. The aim of analysis is to find a direction in the definition domain such that maximizes the mean absolute difference between two values of the objective function calculated at randomly selected points in this direction, or (and) maximizes the mean absolute difference per distance unit of the objective function values calculated at two randomly selected points in this direction. The presented approach requires generating many data sets. Sometimes such a generation is very computation-expensive. Therefore, the ideas discussed in this paper may be applied in the case where the investigator wants not only to solve the extremal problem, but also to discover additional knowledge of it.KeywordsOptimizationvisual analysisanimationdata analysisknowledge discovery

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