Classical and Evolutionary Algorithms in the Optimization of Optical Systems
Classical and Evolutionary Algorithms in the Optimization of Optical Systems by Darko Vasiljevic is a comprehensive exploration published by Springer US on October 23, 2012. This softcover reprint of the original 1st edition from 2002 spans 279 pages and is presented in English. The book delves into the historical context of optimizing optical systems, highlighting the evolution of techniques from traditional mathematical theories to modern methods inspired by natural processes.
Readers will find a detailed examination of how principles of biological evolution can be applied to optimize complex technical systems, particularly in the realm of optical design. The text discusses the challenges faced by lens designers and the advancements in optimization strategies that have emerged in recent years. By bridging the gap between established mathematical approaches and innovative evolutionary algorithms, this work contributes to the fields of computers, artificial intelligence, and information technology, offering insights into the optimization of optical systems.
Official synopsis Publisher
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.
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