Abstract

As the most widely used optimization algorithm in optical design, the damped least square (DLS) method is advantageous for its fast convergence and deterministic optimization path. However, results are strongly dependent on the initial system and problematic when it is stuck in a local minimum in the searching space. To overcome these disadvantages, a biology intelligence-based algorithm, ant colony optimization (ACO) is implemented and tested for optical design tasks. Additionally, the ACO method has a better performance considering glass optimization. Two ACO versions, which are proved applicable, are introduced and their feasibility is assessed based on some case studies.

© 2019 Optical Society of America

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