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Global optimization and structural analysis of Coulomb and logarithmic potentials on the unit sphere using a population-based heuristic approach

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EXPERT SYSTEMS WITH APPLICATIONS 2024年 238卷

作者： Lai, Xiangjing Hao, Jin-Kao Xiao, Renbin Fu, Zhang-Hua Nanjing Univ Posts & Telecommun Inst Adv Technol Nanjing 210023 Peoples R China Univ Angers LERIA 2 Blvd Lavoisier F-49045 Angers France Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Chinese Univ Hong Kong Inst Robot & Intelligent Mfg Shenzhen 518172 Peoples R China

Global optimization of high-dimensional non-convex functions arises in many important applications and researches. In this paper, we focus on the minimum energy configuration problem on the unit sphere, whose goal is to determine the minimum-energy configuration of N particles interacting via the standard Coulomb potential or the discrete logarithmic potential on the unit sphere. This is a classic global optimization problem with many important applications in mathematics, physics, biology and chemistry, and is one of the 18 great mathematical problems for the twenty-first century listed by the Fields Medal winner (Smale, 1998). To determine the minimum-energy configuration for these two potential functions, we propose a population -based global optimization algorithm that combines a two-phase local optimization method with early-stopping strategy, a random perturbation operator, a distance-based population update strategy using a novel distance function to measure the difference between solutions, and a population rebuilding method. Computational results show that the proposed algorithm is very competitive compared to the best known results in the literature. In particular, it improves the best-known result for one instance of the classic Thomson problem (i.e., N = 360) widely studied in the literature. The configurations of instances with up to N = 500 particles are systematically optimized for the first time by the proposed algorithm for the discrete logarithmic potential. The comparative study shows that the putative optimal configurations have a high similarity for the Coulomb and logarithmic potentials and that the defects play an important role in reducing the energy of configuration. The energies of particles on the putative optimal configurations are analyzed for the studied logarithmic potential.

关键词： gradient-based optimization Minimum energy configuration Discrete logarithmic potential Thomson problem Global optimization

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Synergetic use of different evaluation, parameterization and search tools within a multilevel optimization platform

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APPLIED SOFT COMPUTING 2011年第1期11卷 645-651页

作者： Kampolis, Ioannis C. Giannakoglou, Kyriakos C. Natl Tech Univ Athens Lab Thermal Turbomachines Parallel CFD & Optimizat Unit Athens 15710 Greece

This paper presents the synergetic use of different evaluation tools, parameterization schemes and search methods on the levels of a multilevel optimization platform to efficiently solve single-and multi-objective computationally demanding optimization problems. The platform is formed by a number of levels which concurrently search for optimal solutions, by regularly exchanging promising individual solutions. Each level is associated with a problem-specific evaluation tool with its own accuracy and computational cost, a parameterization scheme which determines the design variables and their mapping to generate individual solutions and a search algorithm which is either a metamodel-assisted evolutionary algorithm or a gradient-based method. The use of the multilevel platform with only one of the aforementioned features changing from level to level was presented in a previous paper by the authors. The present paper shows that the combined use of hierarchical evaluation, hierarchical parameterization and hierarchical search decreases further the computational cost by increasing the efficiency of the optimization method. This is demonstrated on function minimization and aerodynamic shape optimization problems;though only two levels are used herein, this is not a restriction and the optimization platform may accommodate any number of them. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Design optimization Evolutionary algorithms Metamodels gradient-based optimization Multilevel algorithm Hierarchical search

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On the efficient optimization of optical properties of particulate monolayers by a hybrid finite element approach

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STRUCTURAL AND MULTIDISCIPLINARY optimization 2021年第3期63卷 1219-1242页

作者： Semmler, Johannes Stingl, Michael Friedrich Alexander Univ Erlangen Nurnberg Lehrstuhl Angew Math Kontinuierliche Optimierung Cauerstr 11 D-91058 Erlangen Germany

This article addresses the numerical simulation and optimization of the optical properties of mono-layered nano-particulate films. The particular optical property of interest is the so-called haze factor, for which a model close to an experimental setup is derived. The numerical solution becomes very involved due to the resulting size of computational domain in comparison to the wave length, rendering the direct simulation method infeasible. As a remedy, a hybrid method is suggested, which in essence consistently combines analytical solutions for the far field with finite element-based solutions for the near field. Using a series of algebraic reformulations, a model with an off- and online component is developed, which results in the computational complexity being reduced by several orders of magnitude. based on the suggested hybrid numerical scheme, which is not limited to the haze factor as objective function, structural optimization problems covering geometrical and topological parametrizations are formulated. These allow the influence of different particle arrangements to be studied. The article is complemented by several numerical experiments underlining the strength of the method.

关键词： Maxwell’ s equation Finite element method Vector spherical harmonics Particle scattering Haze factor gradient-based optimization

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Verification of Implementations of Cryptographic Hash Functions

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IEEE ACCESS 2017年 5卷 7816-7825页

作者： Wang, Dexi Jiang, Yu Song, Houbing He, Fei Gu, Ming Sun, Jiaguang Tsinghua Univ Sch Software Beijing 100084 Peoples R China West Virginia Univ Inst Technol Dept Elect & Comp Engn Montgomery WV 25136 USA

Cryptographic hash functions have become the basis of modern network computing for identity authorization and secure computing;protocol consistency of cryptographic hash functions is one of the most important properties that affect the security and correctness of cryptographic implementations, and protocol consistency should be well proven before being applied in practice. Software verification has seen substantial application in safety-critical areas and has shown the ability to deliver better quality assurance for modern software;thus, applying software verification to a protocol consistency proof for cryptographic hash functions is a reasonable approach to prove their correctness. Verification of protocol consistency of cryptographic hash functions includes modeling of the cryptographic protocol and program analysis of the cryptographic implementation;these require a dedicated cryptographic implementation model that preserves the semantics of the code, efficient analysis of cryptographic operations on arrays and bits, and the ability to verify large-scale implementations. In this paper, we propose a fully automatic software verification framework, VERIHASH, that brings software verification to protocol consistency proofs for cryptographic hash function implementations. It solves the above challenges by introducing a novel cryptographic model design for modeling the semantics of cryptographic hash function implementations, extended array theories for analysis of operations, and compositional verification for scalability. We evaluated our verification framework on two SHA-3 cryptographic hash function implementations: the winner of the NIST SHA-3 competition, Keccack;and an open-source hash program, RHash. We successfully verified the core parts of the two implementations and reproduced a bug in the published edition of RHash.

关键词： Model-predictive control smoothening gradient-based optimization emission control urban traffic control

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High-fidelity multipoint hydrostructural optimization of a 3-D hydrofoil

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JOURNAL OF FLUIDS AND STRUCTURES 2017年 71卷 15-39页

作者： Garg, Nitin Kenway, Gaetan K. W. Martins, Joaquim R. R. A. Young, Yin Lu Univ Michigan Dept Naval Architecture & Marine Engn Ann Arbor MI 48109 USA Univ Michigan Dept Aerosp Engn Ann Arbor MI 48109 USA

The design optimization of flexible hydrofoils and propellers requires coupled hydrodynamic and structural analysis to achieve truly optimal, physically realizable, and structurally sound designs. To address this need, we develop an efficient high-fidelity hydrostructural design optimization approach that can handle large numbers of design variables, multiple design points, as well as design constraints on cavitation, maximum von Mises stress, and manufacturing tolerances. The hydrostructural solver couples a 3-D nearly incompressible Reynolds-averaged Navier-Stokes solver with a 3-D structural finite-element solver. We validate the solver by comparing the hydrodynamic load coefficients and tip bending deformations of a cantilevered aluminum alloy hydrofoil with a NACA 0009 cross section and a trapezoidal planform. We use a coupled adjoint approach for efficient computation of the performance and constraint function derivatives with respect to 210 shape design variables. A single-point hydrostructural optimization of the NACA 0009 baseline hydrofoil yields a 12.4% increase in lift-to-drag ratio, a 2.5% reduction in mass, and a 45% increase in the cavitation inception speed. However, the performance of the single-point optimized hydrofoil is found to be worse than the baseline at off-design conditions. On the other hand, a multipoint optimization yields improved performance over the entire range of expected operating conditions with a weighted average increase in lift-to-drag ratio of 8.5%, and an increased cavitation inception speed of 38%. We compare the hydrostructural optimal result to an equivalent hydrodynamic-only optimization, and we show that only the hydrostructural optimized design satisfies the stress constraint up to the highest expected loading condition, highlighting the need for coupled hydrostructural optimization. The proposed approach enables multipoint optimization of hydrodynamic performance for hydrofoils and marine propulsors with respect to de

关键词： Hydrostructural design optimization gradient-based optimization Cavitation Multipoint optimization Manufacturing constraints Hydrodynamic shape optimization Hydrofoil

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Empirical evaluation of the improved Rprop learning algorithms

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NEUROCOMPUTING 2003年 50卷 105-123页

作者： Igel, C Hüsken, M Ruhr Univ Bochum Inst Neuroinformat D-44780 Bochum Germany

The Rprop algorithm proposed by Riedmiller and Braun is one of the best performing first-order learning methods for neural networks. We discuss modifications of this algorithm that improve its learning speed. The new optimization methods are empirically compared to the existing Rprop variants, the conjugate gradient method, Quickprop, and the BFGS algorithm on a set of neural network benchmark problems. The improved Rprop outperforms the other methods;only the BFGS performs better in the later stages of learning on some of the test problems. For the analysis of the local search behavior, we compare the Rprop algorithms on general hyperparabolic error landscapes, where the new variants confirm their improvement. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： supervised learning resilient backpropagation (Rprop) gradient-based optimization

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Adjoint-based limit cycle oscillation instability sensitivity and suppression

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NONLINEAR DYNAMICS 2023年第4期111卷 3191-3205页

作者： He, Sicheng Jonsson, Eirikur Martins, Joaquim R. R. A. Univ Michigan Aerosp Engn Francois Xavier Bagnoud Aerosp Bldg1320 Beal Ave Ann Arbor MI 48109 USA

Dynamical systems often exhibit limit cycle oscillations (LCOs), self-sustaining oscillations of limited amplitude. LCOs can be supercritical or subcritical. The supercritical response is benign, while the subcritical response can be bi-stable and exhibit a hysteretic response. Subcritical responses can be avoided in design optimization by enforcing LCO stability. However, many high-fidelity system models are computationally expensive to evaluate. Thus, there is a need for an efficient computational approach that can model instability and handle hundreds or thousands of design variables. To address this need, we propose a simple metric to determine the LCO stability using a fitted bifurcation diagram slope. We develop an adjoint-based formula to efficiently compute the stability derivative with respect to many design variables. To evaluate the stability derivative, we only need to compute the time-spectral adjoint equation three times, regardless of the number of design variables. The proposed adjoint method is verified with finite differences, achieving a five-digit agreement between the two approaches. We consider a stability-constrained LCO parameter optimization problem using an analytic model to demonstrate that the optimizer can suppress the instability. We also consider a more realistic LCO speed and stability-constrained airfoil problem that minimizes the normalized mass and stiffness. The proposed method could be extended to optimization problems with a partial differential equation (PDE)-based model, opening the door to other applications where high-fidelity models are needed.

关键词： Adjoint method LCO Stability Time spectral method gradient-based optimization

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Seeding and adjoining zero-halo partitioned parallel scientific codes

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optimization METHODS & SOFTWARE 2020年第3期35卷 618-637页

作者： Mohanamuraly, P. Hascoet, L. Mueller, J. -D. Queen Mary Univ London Sch Engn & Mat Sci London England INRIA Sophia Antipolis TROPICS Team Biot France

Algorithmic differentiation tools can automate the adjoint transformation of parallel message-passing codes [J. Utke, L. Hascoet, P. Heimbach, C. Hill, P. Hovland, and U. Naumann, Toward Adjoinable MPI, in 2009 IEEE International Symposium on Parallel & Distributed Processing, May, IEEE, 2009, pp. 1-8] using the AMPI library. Nevertheless, a non-trivial and manual step after the differentiation is the initialization of the seed and retrieval of the output values from the differentiated code. Ambiguities in seeding occur in programs where the user is unable to expose the complete program flow with a single entry and single exit point to the AD tool. We present the ambiguities associated with seed initialization and output retrieval for adjoint transformation of halo and zero-halo partitioned MPI programs. We introduce a general framework to eliminate ambiguities in seeding and retrieval for shared-node reduction over +, and * operators using a conceptual master-worker model. The model shows the need for new MPI calls for retrieval and eliminate MPI calls for seed initialization. Different implementations for seeding manually assembled adjoints were inferred from the model, namely, partial and unique seeding. We successfully applied the seeding techniques to a 3D zero-halo partitioned unstructured compressible discrete adjoint solver and highlight the merits and demerits of each strategy.

关键词： Algorithmic differentiation adjoint source transformation parallel reverse mode gradient-based optimization fixed-point iteration computational fluid dynamics (CFD) message passing

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An Improved Optimized Model for Invisible Backdoor Attack Creation Using Steganography

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Computers, Materials & Continua 2022年第7期72卷 1173-1193页

作者： Daniyal M.Alghazzawi Osama Bassam J.Rabie Surbhi Bhatia Syed Hamid Hasan Faculty of Computing and Information Technology King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Systems College of Computer Sciences and Information TechnologyKing Faisal UniversitySaudi Arabia

The Deep Neural Networks(DNN)training process is widely affected by backdoor *** backdoor attack is excellent at concealing its identity in the DNN by performing well on regular samples and displaying malicious behavior with data poisoning *** state-of-art backdoor attacks mainly follow a certain assumption that the trigger is sample-agnostic and different poisoned samples use the same *** overcome this problem,in this work we are creating a backdoor attack to check their strength to withstand complex defense strategies,and in order to achieve this objective,we are developing an improved Convolutional Neural Network(ICNN)model optimized using a gradient-based optimization(GBO)(ICNN-GBO)*** the ICNN-GBO model,we are injecting the triggers via a steganography and regularization *** are generating triggers using a single-pixel,irregular shape,and different *** performance of the proposed methodology is evaluated using different performance metrics such as Attack success rate,stealthiness,pollution index,anomaly index,entropy index,and *** the CNN-GBO model is trained with the poisoned dataset,it will map the malicious code to the target *** proposed scheme’s effectiveness is verified by the experiments conducted on both the benchmark datasets namely CIDAR-10 andMSCELEB 1M *** results demonstrate that the proposed methodology offers significant defense against the conventional backdoor attack detection frameworks such as STRIP and Neutral cleanse.

关键词： Convolutional neural network gradient-based optimization steganography backdoor attack and regularization attack

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Actuator energy and drag minimization of a blended-wing-body with variable-camber continuous trailing-edge flaps

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ENGINEERING optimization 2020年第9期52卷 1561-1587页

作者： Zhao, Wei Kapania, Rakesh K. Virginia Polytech Inst & State Univ Kevin T Crofton Dept Aerosp & Ocean Engn Blacksburg VA 24061 USA

This article conducts a multiobjective optimization study for minimizing both the actuator energy and the total drag of a NASA aircraft, the Blended-Wing-Body (BWB), during cruising, by using the three-segment Variable-Camber Continuous Trailing-Edge Flap (VCCTEF) proposed by NASA. The metric for the electric drive actuators' energy for the BWB during cruising is characterized by summing the absolute hinge moments for all actuators. A local minimum is easily obtained for the optimization problem with a least absolute sum cost function when using a gradient-based optimizer. The minimization of the total actuator energy is converted to a linear programming problem by treating the absolute hinge moments as design variables. The induced and profile drags are considered to be the largest two contributions to the total drag. Design variables for the flap rotations and the absolute hinge moments with different orders of magnitude are scaled with respect to their maximum bounds in the optimization study to avoid numerical problems. Different VCCTEF configurations of varying deflection profiles and degrees of actuation independence and traditional flaps are studied and their performance is compared. For the BWB with four representative fuel levels, 80, 50, 20 and 0% of the maximum fuel loads, all during cruising, multiobjective optimization studies show that the VCCTEF with three individual segments can achieve a minimal total drag for the BWB while requiring a minimal total actuator energy to maintain its optimal shape for the minimal total drag.

关键词： Blended-wing-body variable-camber continuous trailing-edge flap actuator energy aerodynamic drag gradient-based optimization

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