Niching in Evolution Strategies and Its Application to Laser Pulse Shaping

Evolutionary Algorithms (EAs), popular search methods for optimization problems, are known for successful and fast location of single optimal solutions. However, many complex search problems require the location and maintenance of multiple solutions. Niching methods, the extension of EAs to address this issue, have been investigated up to date mainly within the field of Genetic Algorithms (GAs), and their applications were limited to low-dimensional search problems. In this paper we present in detail the background for niching methods within Evolution Strategies (ES), and discuss two ES niching methods, which have been introduced recently and have been tested only for theoretical functions. We describe the application of those ES niching methods to a challenging real-life high-dimensional optimization problem, namely Femtosecond Laser Pulse Shaping. The methods are shown to be robust and to achieve satisfying results for the given problem.

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