An algorithm for computationally expensive engineering optimization problems

Abstract

Modern engineering design often relies on computer simulations to evaluate candidate designs, a scenario which results in an optimization of a computationally expensive black-box function. In these settings, there will often exist candidate designs which cause the simulation to fail, and can therefore degrade the search effectiveness. To address this issue, this paper proposes a new metamodel-assisted computational intelligence optimization algorithm which incorporates classifiers into the optimization search. The classifiers predict which candidate designs are expected to cause the simulation to fail, and this prediction is used to bias the search towards designs predicted to be valid. To enhance the search effectiveness, the proposed algorithm uses an ensemble approach which concurrently employs several metamodels and classifiers. A rigorous performance analysis based on a set of simulation-driven design optimization problems shows the effectiveness of the proposed algorithm.     

Co(II) Catalyzed Solvent Free Auto-Oxidation of Methylbenzenes to Substituted Benzoic Acids Under Phase Transfer Conditions

A novel methodology for the solvent free auto-oxidation of methylbenzenes under mild conditions is disclosed. The new scheme is based on a combination of metallic salt (cobalt chloride) and a quaternary ammonium phase transfer catalyst (didecyldimethylammonium bromide) which together form a complex soluble catalyst in the organic phase. Major reaction parameters are studied and optimized and the procedure is applied for the conversion of several substituted toluenes to the corresponding benzoic acids in excellent isolated yields.     

Palladium/Carbon Catalyzed Hydrogen Transfer Reactions using Magnesium/Water as Hydrogen Donor

Results on nonlinear phenomenon (NLP) in the liquid phase hydrogenation of methyl benzoylformate (MBF) and pyruvaldehyde dimethyl acetal (PA) on chiral Pt-cinchona catalyst are reported for the first time (enantiomeric excess 90–95%). The new data support the conclusions of the NLP studies on ethyl pyruvate (EP) and ketopantolactone (KPL). Namely, the order of the adsorption strengths of the parent cinchona alkaloids are: CD > CN > QN ~ QD and the results of the NLP measurements indirectly verify the so-called 1:1 model of enantioselection. The new data, however, call attention to a new, substrate and modifier dependent phenomenon, which necessitates further experiments for a better understanding of the mechanism of the Orito reaction.     

Customizing MRI-Compatible Multifunctional Neural Interfaces through Fiber Drawing

Fiber drawing enables scalable fabrication of multifunctional flexible fibers that integrate electrical, optical, and microfluidic modalities to record and modulate neural activity. Constraints on thermomechanical properties of materials, however, have prevented integrated drawing of metal electrodes with low-loss polymer waveguides for concurrent electrical recording and optical neuromodulation. Here, two fabrication approaches are introduced: 1) an iterative thermal drawing with a soft, low melting temperature (T_m) metal indium, and 2) a metal convergence drawing with traditionally non-drawable high T_m metal tungsten. Both approaches deliver multifunctional flexible neural interfaces with low-impedance metallic electrodes and low-loss waveguides, capable of recording optically-evoked and spontaneous neural activity in mice over several weeks. These fibers are coupled with a light-weight mechanical microdrive (1 g) that enables depth-specific interrogation of neural circuits in mice following chronic implantation. Finally, the compatibility of these fibers with magnetic resonance imaging is demonstrated and they are applied to visualize the delivery of chemical payloads through the integrated channels in real time. Together, these advances expand the domains of application of the fiber-based neural probes in neuroscience and neuroengineering.     

Tuning the Selectivity of Heterogeneous Catalysts: A Trimetallic Approach to Reductive Coupling of Chloroarenes in Water

Reductive homocoupling of chlorobenzenes to the respective biphenyls affords high yields (93–95%), in the presence of catalytic PEG‐400 and 0.4 mol % of a recycleable, heterogeneous trimetallic catalyst (4% Pd, 1% Pt, and 5% Bi on carbon). The competing reduction process is minimized. The catalytic cycle is completed using hydrogen gas, or formate + water or zinc + water mixtures, which generate dihydrogen in situ. Primary kinetic data and some process parameters are studied. The roles of the Pd, Pt, and Bi, different reducing agents, and the phase‐transfer agent are discussed. The reaction mechanism is proposed to depend on the relative concentration of hydride species in the immediate vicinity of the palladium metal.     

Highly Selective Pd‐Catalyzed Reductive Coupling of Substituted Haloarenes with Supported Phase‐Transfer Catalyst using Zn as the Reducing Agent

Highly selective reductive coupling of substituted haloarenes to biaryls is accomplished by Zn in N,N‐dimethylformamide (DMF) and in the presence of a catalytic amount of PdCl₂, PPh₃, and a carbon‐supported phase‐transfer catalyst (PTC). Selectivity as high as 100% is achieved with chlorotoluenes. It is realized that the supported PTC has a predominant role in minimizing the rate of the hydrodehalogenation reaction. The reaction is found to be selective only when homogeneous PdCl₂ is applied as the catalyst, whereas heterogeneous Pd/C‐catalyst selectively reduces chloroarenes to arenes under similar conditions. The role of PPh₃ is discussed and the effects of different process parameters such as temperature, PdCl₂ loading, PPh₃ to PdCl₂ ratio, amount of supported PTC, and solvents have been examined. A mechanism is proposed which is in good agreement with the experimental results obtained.     

A signal processing approach to symmetry detection.

We present an algorithm that detects rotational and reflectional symmetries of two-dimensional objects. Both symmetry types are effectively detected and analyzed using the angular correlation (AC), which measures the correlation between images in the angular direction. The AC is accurately computed using the pseudopolar Fourier transform, which rapidly computes the Fourier transform of an image on a near-polar grid. We prove that the AC of symmetric images is a periodic signal whose frequency is related to the order of the symmetry. This frequency is recovered via spectrum estimation, which is a proven technique in signal processing with a variety of efficient solutions. We also provide a novel approach for finding the center of symmetry and demonstrate the applicability of our scheme to the analysis of real images.     

Predicting behavior: Combining intention with investment.

In recent years, several social researchers have focused on ways to improve the prediction of behavior from attitudes. We examined the use of a measure of investment from the Rusbult and Farrell model of commitment as a means for enhancing prediction in the Ajzen and Fishbein intention model. Analysis of data collected from 95 subjects who were asked about their intention to participate in music-related activities over the next week and month showed that investment and its interaction with intention explain additional behavior variance beyond intention alone. The full model consisting of intention, investment, and their interaction explained, for the one-week period, nearly 53% of the criterion variance, and for the one-month period, nearly 78% of the criterion variance. (PsycINFO Database Record (c) 2010 APA, all rights reserved)