Method and system with optimization of lens module assembly

A method with optimization of a lens module assembly, comprising:

• in preparing a lens module including assembled N lenses respectively formed in cavities to overlap each other on an optical axis, wherein N is a natural number of 2 or more:
• receiving, by a computing system, characteristic information of at least N lenses respectively formed in N cavity groups each including a respective plurality of cavities having a similarity to each other that is higher than a similarity to each other of the assembled N lenses;
• processing, by the computing system, information for selecting N cavities from the N cavity groups, based on a fitness function and the characteristic information;
• and
• processing, by the computing system, angle information on rotation of at least one of N lenses corresponding to the N cavities in a direction around the optical axis, when the N lenses corresponding to the N cavities are assembled to overlap on the optical axis, based on the information for selecting the N cavities,
• wherein the computing system receives or stores a past cavity selection result obtained by the processing of the information for selecting the N cavities, and the fitness function configured based on data of the assembled N lenses or data of the prepared lens module according to the past cavity selection result, and
• wherein the computing system performs updating of the fitness function based on data of each of the N lenses corresponding to the N cavities selected by the processing of the information for selecting the N cavities, and updating of the fitness function based on data of a lens module assembled at an angle corresponding to the processing of the angle information, according to a machine learning algorithm.

A system with optimization of a lens module assembly, comprising:

• at least one processor configured to, in preparing a lens module including assembled N lenses respectively formed in cavities to overlap each other on an optical axis, wherein N is a natural number of 2 or more:
• receive characteristic information of at least N lenses respectively formed in N cavity groups each including a plurality of cavities;
• and
• process information for selecting N cavities from the N cavity groups, based on the characteristic information,
• wherein the system is configured to obtain a past cavity selection result obtained by the processing of the information for selecting the N cavities, a fitness function configured based on data of the assembled N lenses or data of the prepared lens module according to the past cavity selection result, and a genetic algorithm, and
• wherein the at least one processor is further configured to process the information for selecting the N cavities by updating chromosome entity information based on the fitness function and output chromosome information generated by the genetic algorithm from input chromosome information corresponding to the past cavity selection result, and processing the information for selecting the N cavities based on the chromosome entity information and the characteristic information.