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A New Hybrid Equivalent Modeling Method of Low-Frequency Radiation Source Based on GS and JADE algorithms and Phaseless Near-Field Data

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IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY 2024年第3期66卷 917-927页

作者： Huang, Xiaoting Liu, Qifeng Chen, Hao Li, Yongming Huang, Chen Zhu, Xuegui Zhang, Huaiqing Yin, Wen-Yan Chongqing Univ Sch Elect Engn Chongqing 400044 Peoples R China China Ship Dev & Design Ctr Sci & Technol EMC Lab Wuhan 430064 Peoples R China Zhejiang Univ Innovat Inst Electromagnet Informat & Elect Integr Coll Informat Sci & Elect Engn Hangzhou 310027 Peoples R China

Near-field phase measurements are often difficult and very time-consuming for real applications in comparison with phaseless ones. Meanwhile, it is also challenging, with global optimization or phase recovery algorithm implemented, to build an equivalent radiation model based on a dipole array through phaseless near-field data. The optimization and phase recovery algorithms have certain problems in the selections of dipole moment limits and local optimality, respectively. Here, a new hybrid equivalent modeling method of low-frequency radiation characteristics is proposed, which combines the Gerchberg-Saxton (GS) algorithm with adaptive differential evolution algorithm effectively. An initial set of dipole arrays with dipole position, array height, and dipole moment is obtained using the fast solution of the GS algorithm at first, and global optimization algorithm is further used to update the dipole arrays with the global seeking to improve both accuracy and efficiency of the equivalent modeling for the low-frequency radiation source. Such hybrid method can solve the problem of the GS algorithm, which is easy to fall into the local optimum, as well as the problem of global optimization algorithm not being able to quickly determine upper and lower bounds of dipole moments. Its effectiveness is verified by simulations as well as measurements.

关键词： Equivalent dipoles model Gerchberg-Saxton (GS) algorithm global optimization algorithm radiation source

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Discrete intermodal freight transportation network design with route choice behavior of intermodal operators

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2017年 95卷 76-104页

作者： Wang, Xinchang Meng, Qiang Mississippi State Univ Dept Mkt Quantitat Anal & Business Law Mississippi State MS 39762 USA Natl Univ Singapore Dept Civil & Environm Engn Singapore 117576 Singapore

We consider a discrete intermodal network design problem for freight transportation, in which the network planner needs to determine whether or not to build up or expand a link to minimize the total operating cost of carriers and hub operators under a general route choice model of intermodal operators. We formulate the problem as a mixed-integer nonlinear and non-convex program that involves congestion effects, piecewise linear cost functions, and a fixed-point constraint. We develop a series of relaxed and equivalent models to reduce the hardness of the problem and provide theoretical results to show the equivalences. We present two solution methods to solve the problem with one returning heuristic solutions and the other generating a globally optimal solution. We offer two numerical experiments to test the two solution algorithms and also shed light on their performance comparisons. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Freight transportation Intermodal network Economies of scale Congestion effects Route choice model global optimization algorithm

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global resolution of the support vector machine regression parameters selection problem with LPCC

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EURO JOURNAL ON COMPUTATIONAL optimization 2015年第3期3卷 197-261页

作者： Lee, Yu-Ching Pang, Jong-Shi Mitchell, John E. Univ Illinois Urbana IL 61801 USA Univ Southern Calif Los Angeles CA 90089 USA Rensselaer Polytech Inst Troy NY 12180 USA

Support vector machine regression is a robust data fitting method to minimize the sum of deducted residuals of regression, and thus is less sensitive to changes of data near the regression hyperplane. Two design parameters, the insensitive tube size (ee) and the weight assigned to the regression error trading off the normed support vector (Ce), are selected by user to gain better forecasts. The global training and validation parameter selection procedure for the support vector machine regression can be formulated as a bi-level optimization model, which is equivalently reformulated as linear program with linear complementarity constraints (LPCC). We propose a rectangle search global optimization algorithm to solve this LPCC. The algorithm exhausts the invariancy regions on the parameter plane ((Ce, ee)-plane) without explicitly identifying the edges of the regions. This algorithm is tested on synthetic and real-world support vector machine regression problems with up to hundreds of data points, and the efficiency are compared with several approaches. The obtained global optimal parameter is an important benchmark for every other selection of parameters.

关键词： Support vector Machine regression Parameter selection global optimal parameter Mathematical program with complementarity constraints global optimization algorithm

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A novel method to design flexible URAs

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JOURNAL OF OPTICS A-PURE AND APPLIED OPTICS 2007年第5期9卷 502-505页

作者： Lang, Haitao Liu, Liren Yang, Qingguo Beijing Univ Chem Technol Beijing 100029 Peoples R China Chinese Acad Sci Shanghai Inst Opt & Fine Mech Shanghai 201800 Peoples R China

Aperture patterns play a vital role in coded aperture imaging ( CAI) applications. In recent years, many approaches were presented to design optimum or near-optimum aperture patterns. Uniformly redundant arrays (URAs) are, undoubtedly, the most successful for constant sidelobe of their periodic autocorrelation function. Unfortunately, the existing methods can only be used to design URAs with a limited number of array sizes and fixed autocorrelation sidelobe-to-peak ratios. In this paper, we present a novel method to design more flexible URAs. Our approach is based on a searching program driven by DIRECT, a global optimization algorithm. We transform the design question to a mathematical model, based on the DIRECT algorithm, which is advantageous for computer implementation. By changing determinative conditions, we obtain two kinds of types of URAs, including the filled URAs which can be constructed by existing methods and the sparse URAs which have never been mentioned by other authors as far as we know. Finally, we carry out an experiment to demonstrate the imaging performance of the sparse URAs.

关键词： coded aperture imaging filled URAs sparse URAs global optimization algorithm DIRECT

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Feasibility of an inerter-based causal rate-independent damping model for the protection of seismically isolated structures

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STRUCTURES 2024年 62卷

作者： Wu, Zhanzhan Ikago, Kohju Tohoku Univ Grad Sch Engn Sendai 9808572 Japan Tohoku Univ Int Res Inst Disaster Sci Sendai 9808572 Japan 468-1 Aramaki Aza Aoba Aoba Ku Sendai 9808572 Japan

Rate-independent linear damping (RILD), also referred to as linear hysteretic damping, is a linear model of structural or material damping in which the energy dissipation per cycle is independent of the frequency. The resistive force of an ideal RILD model is in phase with the velocity to dissipate energy, while its amplitude is proportional to the displacement, which is suitable for the direct control of seismic response displacement when incorporated into a structure. The tuned Maxwell-Wiechert (TMW) model is a viable option for approximating the damping characteristics of RILD. However, the undesirable stiffness produced by the TMW model compromises the flexibility of the isolator, and thereby fails to deliver the benefits of RILD. To overcome this challenge, the addition of two inerter elements to the TMW model in series and parallel arrangements is proposed in this study to eliminate the undesirable storage stiffness. The parameters of the proposed model are determined using particle swarm optimization. Analyses of a 10-story building structure mounted on linear and nonlinear isolation systems demonstrated that the proposed model achieved lower interstory drifts and approximately 40% reduction in floor response accelerations, with similar isolator displacements compared with LVD when subjected to ground motions dominated by high-frequency components. Moreover, floor response acceleration mitigation was attained at the slight expense of isolator displacement, even when the proposed system was incorporated into nonlinear isolation systems and subjected to low-frequency ground motions.

关键词： Rate-independent linear damping Maxwell-Wiechert model Inerter Low-frequency structure global optimization algorithm Bouc-Wen hysteretic model

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Efficient Biochemical Pathway Prediction Using Simulated Annealing

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IFAC-PapersOnLine 2018年第19期51卷 56-57页

作者： Xu, Zhiqing Mahadevan, Radhakrishnan Department of Chemical Engineering and Applied Chemistry University of Toronto TorontoONM5S3E5 Canada Institute of Biomaterials and Biomedical Engineering University of Toronto TorontoONM5S3G9 Canada

During the past two decades, many computational tools were developed to aid novel biochemical pathway design. However, when longer pathways are to be predicted, putative reaction network with a large number of compounds will be generated after several steps of reactions. The combinatorial growth of the number of compounds makes expansion of the pathway search tree very slow and thus makes the identification of all possible pathways computationally intractable. Although methods based on chemical similarity have been developed to save computation time through reducing the number of nodes and branches in the reaction network according to their structural similarity to the target compound, the method can ignore important pathways containing compounds that are not relatively similar to the target compounds. We here report a new algorithm in our pathway prediction program AnnealPath that improves the performance of pathway prediction in terms of the ability to predict pathways where the intermediates are not similar to the final target compound. We have used a global optimization algorithm, simulated annealing, to improve the efficiency of predicting longer non-linear pathways. We were able to show that our new algorithm is more computationally efficient, generates more possible pathways and identifies a higher number of shorter pathways. © 2018

关键词： Simulated annealing Forecasting global optimization Biochemical pathway Chemical similarity Computation time Computational tools Computationally efficient global optimization algorithm Reaction network Structural similarity

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Efficient and Robust Estimation of Various Ore and Mineral Model Parameters from Residual Gravity Anomalies Using the Dual Classification Learning Rao algorithm

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ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2024年 1-30页

作者： Warnana, Dwa Desa Sungkono, S. Essa, Khalid S. Inst Teknol Sepuluh Nopember Geophys Dept Surabaya 60111 Indonesia Inst Teknol Sepuluh Nopember Fac Sci & Data Analyt Phys Dept Surabaya 60111 Indonesia Cairo Univ Fac Sci Geophys Dept PO 12613 Giza Egypt

The inversion of gravity data aims for fast and accurate parameter estimation associated with subsurface conditions. This step is important for ore and mineral exploration. The inversion problem can be classified as both multimodal and nonlinear, making it a very challenging task. Most existing algorithms, such as very fast simulated annealing, particle swarm optimization, differential evolution, and bat algorithm, involve time-consuming parameter-tuning processes. The Rao algorithm is a global optimization method that provides free parameter-tuning;however, the solutions often get stuck at the local minima. To address the gravity inversion problem, a dual-classification learning Rao algorithm, denoted as DLRao, was proposed. DLRao's exploration and exploitation capacities were enhanced through two operators: modified Rao and adaptive differential evolution. As a result, DLRao does not require any parameter tuning. To showcase its efficiency and robustness, the algorithm was rigorously tested and compared with nine different variants of the Rao algorithms. The evaluation was conducted on two synthetic models: Model-1, representing a horizontal cylinder source, and Model-2, depicting a scenario with multiple anomalous sources. Each model was subjected to two different kinds of noise, namely noise-free and noise-added conditions. Based on convergence and dispersion curves, DLRao outperformed other Rao algorithm variants in terms of efficiency and robustness when applied to gravity data inversion. Utilizing the cost function topography, DLRao is capable of generating a posterior distribution model to effectively manage the uncertainties associated with gravity data inversion. Furthermore, the DLRao algorithm was successfully employed to locate ore and minerals in regions such as Canada, Cuba, and India. The results obtained align well with existing geological studies, drilling data, and findings from published literature.

关键词： Gravity data global optimization algorithm Rao algorithm Posterior distribution model Ore and mineral model

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An Integrated-Circuit Reliability optimization Simulator-XDRS 6

An Integrated-Circuit Reliability Optimization Simulator-XDR...

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2001 6th International Conference on Solid-State and Integrated Circuit Technology(ICSICT-2001)

作者： LIU Hongxia HAO Yue SUN Zhi Microelectronic Institute Xidian University

A new global optimization algorithm is presented in IC reliability simulator *** dominant factor is introduction of NTM(number-theoretic method) and combination of the weighted centroid,the we

ISBN: (纸本)0780365208

A new global optimization algorithm is presented in IC reliability simulator *** dominant factor is introduction of NTM(number-theoretic method) and combination of the weighted centroid,the we

关键词： integrated circuit reliability circuit optimisation circuit simulation number theory integrated circuit modelling hot carriers integrated-circuit reliability optimization simulator XDRS global optimization algorithm IC reliability simulator NTM number-theoretic method weighted centroid weighted reflection quadratic approximation current degradation models substrate current degradation model gate current degradation model HCE hot-carrier induced device degradation circuit lifetime circuit performance two-stage sense amplifier

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optimization of hydrogen distribution network considering pressure and heat recovery 7th

Optimization of hydrogen distribution network considering pr...

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7th International Conference on Applied Energy (ICAE)

作者： Dong, Ruifeng Yu, Yunsong Zhang, Zaoxiao Xi An Jiao Tong Univ State Key Lab Multiphase Flow Power Engn Xian 710049 Peoples R China Xi An Jiao Tong Univ Sch Chem Engn & Technol Xian 710049 Peoples R China

Hydrogen is an important resource in chemical processes. In the hydrogen network, many units are operating at high temperature and pressure, which leads to a large energy change of hydrogen streams. However, the recovery of heat and work in the hydrogen flows has seldom been studied together with the optimization of hydrogen network. It is obviously that the reuse of heat and work energy will raise the effective utilization rate of energy. The recovery of heat could be realized by heat exchangers. The recovery of work will be realized by rotary work exchangers, which are composed of several compressors and turbines with the same shaft. A state space superstructure is adopted to handle all the variables. The mathematical model is built based on exergoeconomic analysis considering both energy and economic factors. The optimization problem will be a mixed integer nonlinear programming (MINLP) problem. The existing algorithms will be improved. A typical refinery hydrogen network is studied as an example. The state space superstructure, exergoeconomic analysis and proposed algorithm could solve the problem competently. The consideration of pressure and heat recovery could reduce the energy consumption and economic cost simultaneously.

关键词： Hydrogen network Heat recovery Work recovery Exergoeconomic analysis global optimization algorithm

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Solving Fractional Problems Management Based on A Deterministic algorithm

Solving Fractional Problems Management Based on A Determinis...

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IITA International Conference on Control, Automation and Systems Engineering

作者： Zhou, Hong Huaiyin Teachers Coll Dept Sci & Technol Huaian Peoples R China

ISBN: (纸本)9780769537283

A new global optimization algorithm is proposed that solves a class of fractional Problems Management (P). In order to generate a tighter linear relaxations for each subproblem and to ensure convergence to a global optimum. The proposed global optimization algorithm which connects the branch and bound method with the cutting-plane method successfully is convergent to the global minimum through the successive refinement of the linear relaxation of the feasible region of the objective function and the solutions of a series of linear relaxation Problems *** our result is slightly more general.

关键词： linearizing method global optimization algorithm feasible region

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