The preface of the book "Evolution and Optimum Seeking" by Hans-Paul Schwefel provides a historical overview of the development of evolution strategies (ESs) in the field of numerical optimization. It begins with the collaboration between two students at the Technical University of Berlin in 1963, who, inspired by natural mutations, developed the concept of ESs. The third student, Peter Bienert, contributed to the construction of an automatic experimenter based on mutation and selection rules. Schwefel, the author, tested these methods using a Zuse Z23 computer, despite initial skepticism and financial challenges. Ingo Rechenberg, one of the students, received his doctorate in 1970 for his thesis on optimizing technical systems using biological evolution principles. The work was further supported by the Deutsche Forschungsgemeinschaft, leading to significant publications and research. The author reflects on the evolution of ESs over 30 years, noting three key points: 1. ESs remain relevant and have seen renewed interest in recent conferences. 2. The computational environment has advanced, with parallel processing becoming more important. 3. The book has been updated to include recent developments in optimization methods such as Genetic Algorithms (GAs), Simulated Annealing (SA), and Tabu Search (TS). The preface also acknowledges the contributions of various individuals who helped with the update and the final publication process. The book is structured into several chapters, covering introduction, problems and methods of optimization, hill climbing strategies, random strategies, evolution strategies for numerical optimization, comparison of direct search strategies, and a summary and outlook. It includes appendices with problem catalogues, program codes, and installation instructions for the programs.The preface of the book "Evolution and Optimum Seeking" by Hans-Paul Schwefel provides a historical overview of the development of evolution strategies (ESs) in the field of numerical optimization. It begins with the collaboration between two students at the Technical University of Berlin in 1963, who, inspired by natural mutations, developed the concept of ESs. The third student, Peter Bienert, contributed to the construction of an automatic experimenter based on mutation and selection rules. Schwefel, the author, tested these methods using a Zuse Z23 computer, despite initial skepticism and financial challenges. Ingo Rechenberg, one of the students, received his doctorate in 1970 for his thesis on optimizing technical systems using biological evolution principles. The work was further supported by the Deutsche Forschungsgemeinschaft, leading to significant publications and research. The author reflects on the evolution of ESs over 30 years, noting three key points: 1. ESs remain relevant and have seen renewed interest in recent conferences. 2. The computational environment has advanced, with parallel processing becoming more important. 3. The book has been updated to include recent developments in optimization methods such as Genetic Algorithms (GAs), Simulated Annealing (SA), and Tabu Search (TS). The preface also acknowledges the contributions of various individuals who helped with the update and the final publication process. The book is structured into several chapters, covering introduction, problems and methods of optimization, hill climbing strategies, random strategies, evolution strategies for numerical optimization, comparison of direct search strategies, and a summary and outlook. It includes appendices with problem catalogues, program codes, and installation instructions for the programs.