@Article{AlbuquerqueSousMont:2016:MuApAu,
author = "Albuquerque, Br{\'a}ulio Fonseca Carneiro de and Sousa, Fabiano
Luis de and Montes, Amauri Silva",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)}",
title = "Multi-objective approach for the automatic design of optical
systems",
journal = "Optics Express",
year = "2016",
volume = "24",
number = "6",
pages = "6619--6643",
month = "Mar.",
keywords = "lgorithms, Design, Economic and social effects, Efficiency, Least
squares approximations, Lenses, Multiobjective optimization,
Optical glass, Optical instrument lenses, Optical systems,
Optimization, Orbits.",
abstract = "An innovative method for the automatic design of optical systems
is presented and verified. The proposed method is based on a
multiobjective evolutionary memetic optimization algorithm. The
multi-objective approach simultaneously, but separately, addresses
the image quality, tolerance, and complexity of the system. The
memetic technique breaks down the search for optical designs in to
three different parts or phases: optical glass selection,
exploration, and exploitation. The optical glass selection phase
defines the most appropriate set of glasses for the system under
design. The glass selection phase limits the available glasses
from hundreds to just a few, drastically reducing the design space
and significantly increasing the efficiency of the automatic
design method. The exploration phase is based on an evolutionary
algorithm (EA), more specifically, on a problem-tailored
generalized extremal optimization (GEO) algorithm, named Optical
GEO (O-GEO). The new EA incorporates many features customized for
lens design, such as optical system codification and diversity
operators. The trade-off systems found in the exploration phase
are refined by a local search, based on the damped least square
method in the exploitation phase. As a result, the method returns
a set of trade-off solutions, generating a Pareto front. Our
method delivers alternative and useful insights for the compromise
solutions in a lens design problem. The efficiency of the proposed
method is verified through realworld examples, showing excellent
results for the tested problems.",
doi = "10.1364/OE.24.006619",
url = "http://dx.doi.org/10.1364/OE.24.006619",
issn = "1094-4087",
language = "en",
urlaccessdate = "02 maio 2024"
}