Darko Vasiljevic – författare

Classical and Evolutionary Algorithms in the Optimization of Optical Systems presents research results in the field of classical and evolutionary algorithms and their application to the optimization of optical systems. This book, which is divided into four parts, illustrates the development of research from the classical least squares method of optimization and its numerous modifications to modern optimization methods that are based on analogies with nature such as genetic algorithms and evolution strategies. Part I describes the mathematical foundations of classical and evolutionary algorithms in the optimization of optical systems. Part II is dedicated to optical design fundamentals. Part III deals with the implementation of the classical and evolutionary algorithms in the program for the optimization of optical systems. Every chapter in this section includes a detailed description of the optimization method with the flow chart diagram. And finally, Part IV presents the results and the discussion of optimization of various types of objectives.Classical and Evolutionary Algorithms in the Optimization of Optical Systems is intended for researchers and post graduate students in the field of optical design who want to learn more about new optimization methods, such as genetic algorithms and evolution strategies, and for those who want to learn more about classical and evolutionary optimization methods and their application to the optimization of optical systems.

The optimization of optical systems is a very old problem. As soon as lens designers discovered the possibility of designing optical systems, the desire to improve those systems by the means of optimization began. For a long time the optimization of optical systems was connected with well-known mathematical theories of optimization which gave good results, but required lens designers to have a strong knowledge about optimized optical systems. In recent years modern optimization methods have been developed that are not primarily based on the known mathematical theories of optimization, but rather on analogies with nature. While searching for successful optimization methods, scientists noticed that the method of organic evolution (well-known Darwinian theory of evolution) represented an optimal strategy of adaptation of living organisms to their changing environment. If the method of organic evolution was very successful in nature, the principles of the biological evolution could be applied to the problem of optimization of complex technical systems.