Title: Design and Convergence Analysis of Evolution Strategies for General Search Spaces: From Integer Evolution Strategies to the Design of Chemical Plants and Building Designs Speakers: Michael Emmerich, Ksenia Pereverdieva Abstract: A major strength of evolutionary algorithms is that they can be applied to general search spaces. To not get trapped in local optima and to reduce bias of the search operators, algorithm designs should adhere to some principles that have been concisely formulated in the work of Rudolph et al. on the design of operators and convergence analysis in general search spaces. After successful implementations of these principles in integer programming by Rudolph, subsequent work extended the scope of this theory to further domains, such as mixed integer search spaces, chemical space, and recently it is applied to design operators for the design of complex building spatial designs based on triangulations of colored graphs. The confluence of topics, such as topology, metric-based evolutionary algorithms, and stochastic convergence analysis makes the design of evolutionary strategies for non-standard representation a fascinating as well as a challenging endeavor.