Thesis (Ph. D.)--University of Rochester. College of Engineering and Applied Science. Institute of Optics, 1992.The demand for lens systems of unconventional forms, coupled with the increased computing power available to most lens designers, has motivated the development of global optimization algorithms for lens design. The successful implementation of such an algorithm requires both a well designed global optimization scheme and an understanding of the special requirements posed by lens design problems. The "simulated annealing" algorithm for global optimization has attracted considerable attention from lens designers; existing variants of simulated annealing, however, lack the desired invariance under linear transformations of the coordi...
Lens system design provides ideal problems for evolutionary algorithms: a complex non-linear optimiz...
The presence of many local minima in the merit function landscape is perhaps the most difficult chal...
The presence of many local minima in the merit function landscape is perhaps the most difficult chal...
A major challenge in lens design is the presence of many local minima in the optimization landscape....
Non-Dominated Sorting Genetic Algorithm 2 (NSGA 2) was used to optimize optical systems with multipl...
Adaptive Optics (AO) improves the efficiency of the optical devices in confocal imaging systems by r...
Simulated annealing is a global optimization method that distinguishes between different local optim...
Computerized ray-tracing has exponentially evolved since its inception. Various software companies h...
A design rule prediction is proposed to assist a lens design in this paper. Deep learning was applie...
An optimization process combining of global optimization algorithm and further optimization treatmen...
Many statistical methods rely on numerical optimization to estimate a model\u27s parameters. Unfortu...
Abstract. Global optimization involves the difficult task of the identification of global extremitie...
Abstract. Significant improvement over a patented lens design is achieved using multi-objective evol...
Adaptive Optics (AO) improves the efficiency of the optical devices in confocal imaging systems by r...
Simulated annealing is an established method for global optimization. Perhaps its most salient featu...
Lens system design provides ideal problems for evolutionary algorithms: a complex non-linear optimiz...
The presence of many local minima in the merit function landscape is perhaps the most difficult chal...
The presence of many local minima in the merit function landscape is perhaps the most difficult chal...
A major challenge in lens design is the presence of many local minima in the optimization landscape....
Non-Dominated Sorting Genetic Algorithm 2 (NSGA 2) was used to optimize optical systems with multipl...
Adaptive Optics (AO) improves the efficiency of the optical devices in confocal imaging systems by r...
Simulated annealing is a global optimization method that distinguishes between different local optim...
Computerized ray-tracing has exponentially evolved since its inception. Various software companies h...
A design rule prediction is proposed to assist a lens design in this paper. Deep learning was applie...
An optimization process combining of global optimization algorithm and further optimization treatmen...
Many statistical methods rely on numerical optimization to estimate a model\u27s parameters. Unfortu...
Abstract. Global optimization involves the difficult task of the identification of global extremitie...
Abstract. Significant improvement over a patented lens design is achieved using multi-objective evol...
Adaptive Optics (AO) improves the efficiency of the optical devices in confocal imaging systems by r...
Simulated annealing is an established method for global optimization. Perhaps its most salient featu...
Lens system design provides ideal problems for evolutionary algorithms: a complex non-linear optimiz...
The presence of many local minima in the merit function landscape is perhaps the most difficult chal...
The presence of many local minima in the merit function landscape is perhaps the most difficult chal...