233 research outputs found

    Effect of Spatial Locality on an Evolutionary Algorithm for Multimodal Optimization

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    Abstract. To explore the effect of spatial locality, crowding differential evolu-tion is incorporated with spatial locality for multimodal optimization. Instead of random trial vector generations, it takes advantages of spatial locality to generate fitter trial vectors. Experiments were conducted to compare the proposed algo-rithm (CrowdingDE-L) with the state-of-the-art algorithms. Further experiments were also conducted on a real world problem. The experimental results indicate that CrowdingDE-L has a competitive edge over the other algorithms tested.

    Multimodal estimation of distribution algorithms

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    Taking the advantage of estimation of distribution algorithms (EDAs) in preserving high diversity, this paper proposes a multimodal EDA. Integrated with clustering strategies for crowding and speciation, two versions of this algorithm are developed, which operate at the niche level. Then these two algorithms are equipped with three distinctive techniques: 1) a dynamic cluster sizing strategy; 2) an alternative utilization of Gaussian and Cauchy distributions to generate offspring; and 3) an adaptive local search. The dynamic cluster sizing affords a potential balance between exploration and exploitation and reduces the sensitivity to the cluster size in the niching methods. Taking advantages of Gaussian and Cauchy distributions, we generate the offspring at the niche level through alternatively using these two distributions. Such utilization can also potentially offer a balance between exploration and exploitation. Further, solution accuracy is enhanced through a new local search scheme probabilistically conducted around seeds of niches with probabilities determined self-adaptively according to fitness values of these seeds. Extensive experiments conducted on 20 benchmark multimodal problems confirm that both algorithms can achieve competitive performance compared with several state-of-the-art multimodal algorithms, which is supported by nonparametric tests. Especially, the proposed algorithms are very promising for complex problems with many local optima

    Roadmap on holography

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    From its inception holography has proven an extremely productive and attractive area of research. While specific technical applications give rise to 'hot topics', and three-dimensional (3D) visualisation comes in and out of fashion, the core principals involved continue to lead to exciting innovations in a wide range of areas. We humbly submit that it is impossible, in any journal document of this type, to fully reflect current and potential activity; however, our valiant contributors have produced a series of documents that go no small way to neatly capture progress across a wide range of core activities. As editors we have attempted to spread our net wide in order to illustrate the breadth of international activity. In relation to this we believe we have been at least partially successful.This work was supported by Ministerio de EconomĂ­a, Industria y Competitividad (Spain) under projects FIS2017-82919-R (MINECO/AEI/FEDER, UE) and FIS2015-66570-P (MINECO/FEDER), and by Generalitat Valenciana (Spain) under project PROMETEO II/2015/015

    Adaptive multimodal continuous ant colony optimization

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    Seeking multiple optima simultaneously, which multimodal optimization aims at, has attracted increasing attention but remains challenging. Taking advantage of ant colony optimization algorithms in preserving high diversity, this paper intends to extend ant colony optimization algorithms to deal with multimodal optimization. First, combined with current niching methods, an adaptive multimodal continuous ant colony optimization algorithm is introduced. In this algorithm, an adaptive parameter adjustment is developed, which takes the difference among niches into consideration. Second, to accelerate convergence, a differential evolution mutation operator is alternatively utilized to build base vectors for ants to construct new solutions. Then, to enhance the exploitation, a local search scheme based on Gaussian distribution is self-adaptively performed around the seeds of niches. Together, the proposed algorithm affords a good balance between exploration and exploitation. Extensive experiments on 20 widely used benchmark multimodal functions are conducted to investigate the influence of each algorithmic component and results are compared with several state-of-the-art multimodal algorithms and winners of competitions on multimodal optimization. These comparisons demonstrate the competitive efficiency and effectiveness of the proposed algorithm, especially in dealing with complex problems with high numbers of local optima

    Recent Advances and Future Trends in Nanophotonics

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    Nanophotonics has emerged as a multidisciplinary frontier of science and engineering. Due to its high potential to contribute to breakthroughs in many areas of technology, nanophotonics is capturing the interest of many researchers from different fields. This Special Issue of Applied Sciences on “Recent advances and future trends in nanophotonics” aims to give an overview on the latest developments in nanophotonics and its roles in different application domains. Topics of discussion include, but are not limited to, the exploration of new directions of nanophotonic science and technology that enable technological breakthroughs in high-impact areas mainly regarding diffraction elements, detection, imaging, spectroscopy, optical communications, and computing

    Roadmap on holography

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    From its inception holography has proven an extremely productive and attractive area of research. While specific technical applications give rise to 'hot topics', and three-dimensional (3D) visualisation comes in and out of fashion, the core principals involved continue to lead to exciting innovations in a wide range of areas. We humbly submit that it is impossible, in any journal document of this type, to fully reflect current and potential activity; however, our valiant contributors have produced a series of documents that go no small way to neatly capture progress across a wide range of core activities. As editors we have attempted to spread our net wide in order to illustrate the breadth of international activity. In relation to this we believe we have been at least partially successful

    Optimization of the holographic process for imaging and lithography

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 272-297).Since their invention in 1948 by Dennis Gabor, holograms have demonstrated to be important components of a variety of optical systems and their implementation in new fields and methods is expected to continue growing. Their ability to encode 3D optical fields on a 2D plane opened the possibility of novel applications for imaging and lithography. In the traditional form, holograms are produced by the interference of a reference and object waves recording the phase and amplitude of the complex field. The holographic process has been extended to include different recording materials and methods. The increasing demand for holographic-based systems is followed by a need for efficient optimization tools designed for maximizing the performance of the optical system. In this thesis, a variety of multi-domain optimization tools designed to improve the performance of holographic optical systems are proposed. These tools are designed to be robust, computationally efficient and sufficiently general to be applied when designing various holographic systems. All the major forms of holographic elements are studied: computer generated holograms, thin and thick conventional holograms, numerically simulated holograms and digital holograms. Novel holographic optical systems for imaging and lithography are proposed. In the case of lithography, a high-resolution system based on Fresnel domain computer generated holograms (CGHs) is presented. The holograms are numerically designed using a reduced complexity hybrid optimization algorithm (HOA) based on genetic algorithms (GAs) and the modified error reduction (MER) method. The algorithm is efficiently implemented on a graphic processing unit. Simulations as well as experimental results for CGHs fabricated using electron-beam lithography are presented. A method for extending the system's depth of focus is proposed. The HOA is extended for the design and optimization of multispectral CGHs applied for high efficiency solar concentration and spectral splitting. A second lithographic system based on optically recorded total internal reflection (TIR) holograms is studied. A comparative analysis between scalar and (cont.) vector diffraction theories for the modeling and simulation of the system is performed.A complete numerical model of the system is conducted including the photoresist response and first order models for shrinkage of the holographic emulsion. A novel block-stitching algorithm is introduced for the calculation of large diffraction patterns that allows overcoming current computational limitations of memory and processing time. The numerical model is implemented for optimizing the system's performance as well as redesigning the mask to account for potential fabrication errors. The simulation results are compared to experimentally measured data. In the case of imaging, a segmented aperture thin imager based on holographically corrected gradient index lenses (GRIN) is proposed. The compound system is constrained to a maximum thickness of 5mm and utilizes an optically recorded hologram for correcting high-order optical aberrations of the GRIN lens array. The imager is analyzed using system and information theories. A multi-domain optimization approach is implemented based on GAs for maximizing the system's channel capacity and hence improving the information extraction or encoding process. A decoding or reconstruction strategy is implemented using the superresolution algorithm. Experimental results for the optimization of the hologram's recording process and the tomographic measurement of the system's space-variant point spread function are presented. A second imaging system for the measurement of complex fluid flows by tracking micron sized particles using digital holography is studied. A stochastic theoretical model based on a stability metric similar to the channel capacity for a Gaussian channel is presented and used to optimize the system. The theoretical model is first derived for the extreme case of point source particles using Rayleigh scattering and scalar diffraction theory formulations. The model is then extended to account for particles of variable sizes using Mie theory for the scattering of homogeneous dielectric spherical particles. The influence and statistics of the particle density dependent cross-talk noise are studied. Simulation and experimental results for finding the optimum particle density based on the stability metric are presented. For all the studied systems, a sensitivity analysis is performed to predict and assist in the correction of potential fabrication or calibration errors.by José Antonio Domínguez-Caballero.Ph.D

    Roadmap on structured light

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    Structured light refers to the generation and application of custom light fields. As the tools and technology to create and detect structured light have evolved, steadily the applications have begun to emerge. This roadmap touches on the key fields within structured light from the perspective of experts in those areas, providing insight into the current state and the challenges their respective fields face. Collectively the roadmap outlines the venerable nature of structured light research and the exciting prospects for the future that are yet to be realized
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