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Search results for: SURROGATE-ASSISTED OPTIMIZATION,UNCERTAINTY QUANTIFICATION,DOMAIN CONFINEMENT,YIELD OPTIMIZATION,STATISTICAL ANALYSIS
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Performance-driven yield optimization of high-frequency structures by kriging surrogates
PublicationUncertainty quantification is an important aspect of engineering design, as manufacturing toler-ances may affect the characteristics of the structure. Therefore, quantification of these effects is in-dispensable for adequate assessment of the design quality. Toward this end, statistical analysis is performed, for reliability reasons, using full-wave electromagnetic (EM) simulations. Still, the computational expenditures associated...
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Expedited Yield Optimization of Narrow- and Multi-Band Antennas Using Performance-Driven Surrogates
PublicationUncertainty quantification is an important aspect of engineering design, also pertaining to the development and performance evaluation of antenna systems. Manufacturing tolerances as well as other types of uncertainties, related to material parameters (e.g., substrate permittivity) or operating conditions (e.g., bending) may affect the antenna characteristics. In the case of narrow- or multi-band antennas, this usually leads to...
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Reliable Surrogate Modeling of Antenna Input Characteristics by Means of Domain Confinement and Principal Components
PublicationA reliable design of contemporary antenna structures necessarily involves full-wave electromagnetic (EM) analysis which is the only tool capable of accounting, for example, for element coupling or the effects of connectors. As EM simulations tend to be CPU-intensive, surrogate modeling allows for relieving the computational overhead of design tasks that require numerous analyses, for example, parametric optimization or uncertainty...
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Expedited Yield-Driven Design of High-Frequency Structures by Kriging Surrogates in Confined Domains
PublicationUncertainty quantification is an important aspect of engineering design, also pertaining to the development and performance evaluation of high-frequency structures systems. Manufacturing tolerances as well as other types of uncertainties, related to material parameters (e.g., substrate permittivity) or operating conditions (e.g., bending) may affect the characteristics of antennas or microwave devices. For example, in the case...
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Rapid tolerance‐aware design of miniaturized microwave passives by means of confined‐domain surrogates
PublicationThe effects of uncertainties, primarily manufacturing tolerances but also incomplete information about operating conditions or material parameters, can be detrimental to the performance of microwave components. Quantification of such effects is essential to ensure a meaningful evaluation of the structure, in particular, its reliability under imperfect fabrication procedures. The improvement of the circuit robustness can be achieved...
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Tolerance-Aware Optimization of Microwave Circuits by Means of Principal Directions and Domain-Restricted Metamodels
PublicationPractical microwave design is most often carried out in the nominal sense. Yet, in some cases, performance degradation due to uncertainties may lead to the system failing to meet the prescribed specifications. Reliable uncertainty quantification (UQ) is therefore important yet intricate from numerical standpoint, especially when the circuit at hand is to be evaluated using electromagnetic (EM) simulation tools. Tolerance-aware...
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Low-Cost Yield-Driven Design of Antenna Structures Using Response-Variability Essential Directions and Parameter Space Reduction
PublicationQuantifying the effects of fabrication tolerances and uncertainties of other types is fundamental to improve antenna design immunity to limited accuracy of manufacturing procedures and technological spread of material parameters. This is of paramount importance especially for antenna design in the industrial context. Degradation of electrical and field properties due to geometry parameter deviations often manifests itself as, e.g.,...
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Accurate Modeling of Antenna Structures by Means of Domain Confinement and Pyramidal Deep Neural Networks
PublicationThe importance of surrogate modeling techniques has been gradually increasing in the design of antenna structures over the recent years. Perhaps the most important reason is a high cost of full-wave electromagnetic (EM) analysis of antenna systems. Although imperative in ensuring evaluation reliability, it entails considerable computational expenses. These are especially pronounced when carrying out EM-driven design tasks such...
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Recent advances in high-frequency modeling by means of domain confinement and nested kriging
PublicationDevelopment of modern high-frequency components and circuits is heavily based on full-wave electromagnetic (EM) simulation tools. Some phenomena, although important from the point of view of the system performance, e.g., EM cross-coupling effects, feed radiation in antenna arrays, substrate anisotropy, cannot be adequately accounted for using simpler means such as equivalent network representations. Consequently, the involvement...
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Tolerance Optimization of Antenna Structures by Means of Response Feature Surrogates
PublicationFabrication tolerances and other types of uncertainties, e.g., the lack of precise knowledge of material parameters, have detrimental effects on electrical and field performance of antenna systems. In the case of input characteristics these are particularly noticeable for narrow- and multi-band antennas where deviations of geometry parameters from their nominal values lead to frequency shifts of the operating frequency bands. Improving...
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Design-Oriented Two-Stage Surrogate Modeling of Miniaturized Microstrip Circuits with Dimensionality Reduction
PublicationContemporary microwave design heavily relies on full-wave electromagnetic (EM) simulation tools. This is especially the case for miniaturized devices where EM cross-coupling effects cannot be adequately accounted for using equivalent network models. Unfortunately, EM analysis incurs considerable computational expenses, which becomes a bottleneck whenever multiple evaluations are required. Common simulation-based design tasks include...
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Design-oriented modeling of antenna structures by means of two-level kriging with explicit dimensionality reduction
PublicationThe employment of full-wave electromagnetic (EM) analysis is a practical necessity in the design of contemporary antenna structures. This is because simpler models are generally not available or of limited accuracy. At the same time, EM-based design is computationally expensive. Consequently, the ways of accelerating tasks such as parametric optimization or uncertainty quantification have to be sought. A possible workaround that...
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Expedited Acquisition of Database Designs for Reduced-Cost Performance-Driven Modeling and Rapid Dimension Scaling of Antenna Structures
PublicationFast replacement models have been playing an increasing role in high-frequency electronics, including the design of antenna structures. Their role is to improve computational efficiency of the procedures that normally entail large numbers of expensive full-wave electromagnetic (EM) simulations, e.g., parametric optimization or uncertainty quantification. Recently introduced performance-driven modeling methods, such as the nested...
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Rapid Yield Estimation and Optimization of Microwave Structures Exploiting Feature-Based Statistical Analysis
PublicationIn this paper, we propose a simple, yet reliable methodology to expediteyield estimation and optimization of microwave structures. In our approach,the analysis of the entire response of the structure at hand (e.g., $S$-parameters asa function of frequency) is replaced by response surface modeling of suitablyselected feature points. On the one hand, this is sufficient to determinewhether a design satisfies given performance specifications....
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Scalability of surrogate-assisted multi-objective optimization of antenna structures exploiting variable-fidelity electromagnetic simulation models
PublicationMulti-objective optimization of antenna structures is a challenging task due to high-computational cost of evaluating the design objectives as well as large number of adjustable parameters. Design speedup can be achieved by means of surrogate-based optimization techniques. In particular, a combination of variable-fidelity electromagnetic (EM) simulations, design space reduction techniques, response surface approximation (RSA) models,...
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Accelerated multi-objective design optimization of antennas by surrogate modeling and domain segmentation
PublicationMulti-objective optimization yields indispensable information about the best possible design trade-offs of an antenna structure, yet it is challenging if full-wave electromagnetic (EM) analysis is utilized for performance evaluation. The latter is a necessity for majority of contemporary antennas as it is the only way of achieving acceptable modeling accuracy. In this paper, a procedure for accelerated multi-objective design of...
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Rapid surrogate-assisted statistical analysis of compact microstrip couplers
PublicationIn this paper, a technique for low-cost statistical analysis and yield estimation of compact microwave couplers has been presented. The analysis is executed at the level of a fast surrogate model representing selected characteristic points of the coupler response that are critical to determine satisfaction/violation of the prescribed design specifications. Because of less nonlinear dependence of the characteristic points on geometry...
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Fast multi-criterial statistical analysis and design optimization of compact microwave couplers
Publication—A rapid statistical analysis and yield estimation of compact microwave couplers involving multiple performance parameters has been presented. The analysis is realized using a fast surrogate model representing appropriate characteristic points of the coupler response. Because of less nonlinear dependence of the characteristic points on the structure geometry (compared to the original response, i.e., S-parameters vs. frequency),...
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Computationally-Efficient Statistical Design and Yield Optimization of Resonator-Based Notch Filters Using Feature-Based Surrogates
PublicationModern microwave devices are designed to fulfill stringent requirements pertaining to electrical performance, which requires, among others, a meticulous tuning of their geometry parameters. When moving up in frequency, physical dimensions of passive microwave circuits become smaller, making the system performance increasingly susceptible to manufacturing tolerances. In particular, inherent inaccuracy of fabrication processes affect...
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A Multi-Fidelity Surrogate-Model-Assisted Evolutionary Algorithm for Computationally Expensive Optimization Problems
PublicationIntegrating data-driven surrogate models and simulation models of different accuracies (or fideli-ties) in a single algorithm to address computationally expensive global optimization problems has recently attracted considerable attention. However, handling discrepancies between simulation models with multiple fidelities in global optimization is a major challenge. To address it, the two major contributions of this paper include:...
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Surrogate Modeling and Optimization Using Shape-Preserving Response Prediction: A Review
PublicationComputer simulation models are ubiquitous in modern engineering design. In many cases, they are the only way to evaluate a given design with sufficient fidelity. Unfortunately, an added computa-tional expense is associated with higher fidelity models. Moreover, the systems being considered are often highly nonlinear and may feature a large number of designable parameters. Therefore, it may be impractical to solve the design problem...
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Nested Kriging with Variable Domain Thickness for Rapid Surrogate Modeling and Design Optimization of Antennas
PublicationDesign of modern antennas faces numerous difficulties, partially rooted in stringent specifications imposed on both electrical and field characteristics, demands concerning various functionalities (circular polarization, pattern diversity, band-notch operation), but also constraints imposed upon the physical size of the radiators. Conducting the design process at the level of full-wave electromagnetic (EM) simulations, otherwise...
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Statistical analysis and robust design of circularly polarized antennas using sequential approximate optimization
PublicationIn the paper, reliable yield estimation and tolerance-aware design optimization of circular polarization (CP) antennas is discussed. We exploit auxiliary kriging interpolation models established in the vicinity of the nominal design in order to speed up the process of statistical analysis of the antenna structure at hand. Sequential approximate optimization is then applied to carry out robust design of the antenna, here, oriented...
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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublicationIn this work, a computationally efficient method based on data driven surrogate models is pro-posed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna acts as a as module that simultaneously pre-filters unwanted sig-nals, and enhances the desired signals at the operating frequency. However, due to a typically large number of design variables of FSS unit elements,...
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Efficient uncertainty quantification using sequential sampling-based neural networks
PublicationUncertainty quantification (UQ) of an engineered system involves the identification of uncertainties, modeling of the uncertainties, and the forward propagation of the uncertainties through a system analysis model. In this work, a novel surrogate-based forward propagation algorithm for UQ is proposed. The proposed algorithm is a new and unique extension of the recent efficient global optimization using neural network (NN)-based...
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Business Process Analysis and Optimization 2022
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Business Process Analysis and Optimization 2023
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Three-objective antenna optimization by means of kriging surrogates and domain segmentation
PublicationIn this paper, an optimization framework for multi-objective design of antenna structures is discussed which exploits data-driven surrogates, a multi-objective evolutionary algorithm, response correction techniques for design refinement, as well as generalized domain segmentation. The last mechanism is introduced to constrain the design space region subjected to sampling, which permits reduction of the number of training data samples...
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Multi-fidelity robust aerodynamic design optimization under mixed uncertainty
PublicationThe objective of this paper is to present a robust optimization algorithm for computationally efficient airfoil design under mixed (inherent and epistemic) uncertainty using a multi-fidelity approach. This algorithm exploits stochastic expansions derived from the Non-Intrusive Polynomial Chaos (NIPC) technique to create surrogate models utilized in the optimization process. A combined NIPC expansion approach is used, where both...
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Fast surrogate-assisted simulation-driven design of compact microwave hybrid couplers
PublicationThis work presents a robust methodology for expedited simulation-driven design optimization of compact microwave hybrid couplers. The technique relies on problem decomposition, and a bot-tom–up design strategy, starting from the level of basic building blocks of the coupler, and finishing with a tuning procedure that exploits a fast surrogate model of the entire structure. The latter is constructed by cascading local response surface...
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Optimization of Single-Sided Lapping Kinematics Based on Statistical Analysis of Abrasive Particles Trajectories
PublicationThe chapter presents the influence of selected kinematic parameters on the geometrical results of the single-sided lapping process. The optimization of these parameters is aimed at improving the quality and flatness of the machined surfaces. The uniformity of tool wear was assumed as main optimization criterion. Lapping plate wear model was created and in detail was analyzed. A Matlab program was designed to simulate the abrasive...
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Domain segmentation for low-cost surrogate-assisted multi-objective design optimisation of antennas
PublicationAbstract: Information regarding the best possible design trade-offs of an antenna structure can be obtained through multiobjective optimisation (MO). Unfortunately, MO is extremely challenging if full-wave electromagnetic (EM) simulation models are used for performance evaluation. Yet, for the majority of contemporary antennas, EM analysis is the only tool that ensures reliability. This study introduces a procedure for accelerated...
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On Decomposition-Based Surrogate-Assisted Optimization of Leaky Wave Antenna Input Characteristics for Beam Scanning Applications
PublicationRecent years have witnessed a growing interest in reconfigurable antenna systems. Travelling wave antennas (TWAs) and leaky wave antennas (LWAs) are representative examples of structures featuring a great level of flexibility (e.g., straightforward implementation of beam scanning), relatively simple geometrical structure, low profile, and low fabrication cost. Notwithstanding, the design process of TWAs/LWAs is a challenging endeavor...
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Multi-objective design optimization of antenna structures using sequential domain patching with automated patch size deter-mination
PublicationIn this paper, a simple yet efficient and reliable technique for fully automated multi-objective design optimization of antenna structures using sequential domain patching (SDP) is discussed. The optimization procedure according to SDP is a two-step process: (i) obtaining the initial set of Pareto-optimal designs representing the best possible trade-offs between considered conflicting objectives, and (ii) Pareto set refinement...
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Multi-Fidelity Local Surrogate Model for Computationally Efficient Microwave Component Design Optimization
PublicationIn order to minimize the number of evaluations of high-fidelity (“fine”) model in the optimization process, to increase the optimization speed, and to improve optimal solution accuracy, a robust and computational-efficient multi-fidelity local surrogate-model optimization method is proposed. Based on the principle of response surface approximation, the proposed method exploits the multi-fidelity coarse models and polynomial interpolation...
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Rapid Yield Optimization of Miniaturized Microwave Passives by Response Features and Variable-Fidelity EM Simulations
PublicationThe operation of high-frequency devices, including microwave passive components, can be impaired by fabrication tolerances but also incomplete knowledge concerning operating conditions (temperature, input power levels) and material parameters (e.g., substrate permittivity). Although the accuracy of manufacturing processes is always limited, the effects of parameter deviations can be accounted for in advance at the design phase...
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Two-Stage Variable-Fidelity Modeling of Antennas with Domain Confinement
PublicationSurrogate modeling has become the method of choice in solving an increasing number of antenna design tasks, especially those involving expensive full-wave electromagnetic (EM) simulations. Notwithstanding, the curse of dimensionality considerably affects conventional metamodeling methods, and their capability to efficiently handle nonlinear antenna characteristics over broad ranges of the system parameters is limited. Performance-driven...
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Variable‐fidelity modeling of antenna input characteristics using domain confinement and two‐stage Gaussian process regression surrogates
PublicationThe major bottleneck of electromagnetic (EM)-driven antenna design is the high CPU cost of massive simulations required by parametric optimization, uncertainty quantification, or robust design procedures. Fast surrogate models may be employed to mitigate this issue to a certain extent. Unfortunately, the curse of dimensionality is a serious limiting factor, hindering the construction of conventional data-driven models valid over...
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Model Correction and Optimization Framework for Expedited EM-Driven Surrogate-Assisted Design of Compact Antennas
PublicationDesign of compact antennas is a numerically challenging process that heavily relies on electromagnetic (EM) simulations and numerical optimization algorithms. For reliability of simulation results, EM models of small radiators often include connectors which—despite being components with fixed dimensions—significantly contribute to evaluation cost. In this letter, a response correction method for antenna models without connector,...
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Variable-fidelity response feature surrogates for accelerated statistical analysis and yield estimation of compact microwave components
PublicationAccounting for manufacturing tolerances is an essential part of a reliable microwave design process. Yet, quantification of geometry and/or material parameter uncertainties is challenging at the level of full-wave electromagnetic (EM) simulation models. This is due to inherently high cost of EM analysis and massive simulations necessary to conduct the statistical analysis. Here, a low-cost and accurate yield estimation procedure...
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What entrepreneurs think about tax optimization?
Open Research DataThe study conducted on a group of 259 entrepreneurs concerned the behavioral attitudes of business owners regarding their opinion on tax optimization. From the study we will learn, among others, how tax optimization is defined according to entrepreneurs, their attitude towards it, as well as what optimization actions they have taken so far.
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Rapid Microwave Design Optimization in Frequency Domain Using Adaptive Response Scaling
PublicationIn this paper, a novel methodology for cost-efficient microwave design optimization in the frequency domain is proposed. Our technique, referred to as adaptive response scaling (ARS), has been developed for constructing a fast replacement model (surrogate) of the high-fidelity electromagnetic-simulated model of the microwave structure under design using its equivalent circuit (low-fidelity model). The basic principle of ARS is...
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Reduced-Cost Two-Level Surrogate Antenna Modeling using Domain Confinement and Response Features
PublicationElectromagnetic (EM) simulation tools have become indispensable in the design of contemporary antennas. Still, the major setback of EM-driven design is the associated computational overhead. This is because a single full-wave simulation may take from dozens of seconds up to several hours, thus, the cost of solving design tasks that involve multiple EM analyses may turn unmanageable. This is where faster system representations (surrogates)...
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Low-Cost Behavioral Modeling of Antennas by Dimensionality Reduction and Domain Confinement
PublicationBehavioral modeling has been rising in importance in modern antenna design. It is primarily employed to diminish the computational cost of procedures involving massive full-wave electromagnetic (EM) simulations. Cheaper alternative offer surrogate models, yet, setting up data-driven surrogates is impeded by, among others, the curse of dimensionality. This article introduces a novel approach to reduced-cost surrogate modeling of...
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Small Antenna Design Using Surrogate-Based Optimization
PublicationIn this work, design of small antennas using efficient numerical optimization is investigated. We exploit variable-fidelity electromagnetic (EM) simulations and the adaptively adjusted design specifications (AADS) technique. Combination of these methods allows us to simultaneously adjust multiple geometry parameters of the antenna structure of interest in a computationally feasible manner, leading to substantial reduction of the...
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Expedited design of microstrip antenna subarrays using surrogate-based optimization
PublicationComputationally efficient simulation-driven design of microstrip antenna subarrays is presented. The proposed design approach aims at simultaneous adjustment of all relevant geometry parameters of the subarray, which allows us to take into account the effect of the feeding network on the subarray radiation pattern (in particular, the side lobe level, SLL). In order to handle a large number of variables involved in the design process,...
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ENGINEERING OPTIMIZATION
Journals -
Uncertainty Quantification in Experimental Structural Dynamics Identification of Composite Material Structures
PublicationComposite materials are widely used in manufacture of aerospace and wind energy structural components. These load carrying structures are subjected to dynamic time-varying loading conditions. Robust structural dynamics identification procedure impose tight constraints on the quality of modal models estimates obtained from vibration experiments. Modal testing results are influenced by numerous factors introducing uncertainty to...
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Multi-objective optimization of microwave couplers using corrected domain patching
PublicationPractical design of microwave components and circuits is a compromise between various, often conflicting objectives. In case of compact structures, the trade-offs are typically concerned with the circuit size and its electrical performance. Comprehensive information about the best possible trade-offs can be obtained by means of multi-objective optimization. In this paper, we propose a computationally efficient technique for identifying...
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Fast Low-fidelity Wing Aerodynamics Model for Surrogate-Based Shape Optimization
PublicationVariable-fidelity optimization (VFO) can be efficient in terms of the computational cost when compared with traditional approaches, such as gradient-based methods with adjoint sensitivity information. In variable-fidelity methods, the directoptimization of the expensive high-fidelity model is replaced by iterative re-optimization of a physics-based surrogate model, which is constructed from a corrected low-fidelity model. The success...