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13th IEEE congress on Evolutionary computation, CEC 2024

作者： Shu, Tianye Nan, Yang Shang, Ke Ishibuchi, Hisao Southern University of Science and Technology Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Shenzhen518055 China Southern University of Science and Technology Shenzhen518055 China Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China

ISBN: (纸本)9798350308365

For evolutionary multi-objective optimization algorithms (EMOAs), an external archive can be utilized for saving good solutions found throughout the evolutionary process. Recent studies showed that a solution set selected from an external archive is usually superior to the final population. That is, the incorporation of an external archive improves the performance of EMOAs. However, the computation time for maintaining an external archive is long, especially when the archive size is large. To solve this issue, a simple archiving strategy is to save all solutions generated in the last several generations. In this paper, we examine this archiving strategy for three representative EMOAs on artificial test problems (Minus-DTLZ and WFG) and real-world problems (RE). Our results show that archiving the last several generations clearly improves the performance of EMOAs without severely increasing the computation time. © 2024 IEEE.

关键词： Optimization algorithms

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Practical homomorphic encryption over the integers for secure computation in the cloud

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international JOURNAL OF INFORMATION SECURITY 2019年第5期18卷 549-579页

作者： Dyer, James Dyer, Martin Xu, Jie De Montfort Univ Leicester Leics England Univ Leeds Sch Comp Leeds W Yorkshire England

We present novel homomorphic encryption schemes for integer arithmetic, intended primarily for use in secure single-party computation in the cloud. These schemes are capable of securely computing arbitrary degree polynomials homomorphically. In practice, ciphertext size and running times limit the polynomial degree, but this appears sufficient for most practical applications. We present four schemes, with increasing levels of security, but increasing computational overhead. Two of the schemes provide strong security for high-entropy data. The remaining two schemes provide strong security regardless of this assumption. These four algorithms form the first two levels of a hierarchy of schemes, and we also present the general cases of each scheme. We further elaborate how a fully homomorphic system can be constructed from one of our general cases. In addition, we present a variant based upon Chinese Remainder Theorem secret sharing. We detail extensive evaluation of the first four algorithms of our hierarchy by computing low-degree polynomials. The timings of these computations are extremely favourable by comparison with even the best of existing methods and dramatically outperform many well-publicised schemes. The results clearly demonstrate the practical applicability of our schemes.

关键词： Cryptography Symmetric encryption Homomorphic encryption Computing on encrypted data Secure computation in the cloud

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A Quality Diversity Study in EvoDevo Processes for engineering Design 13

A Quality Diversity Study in EvoDevo Processes for Engineeri...

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13th IEEE congress on Evolutionary computation, CEC 2024

作者： Buchanan, Edgar Hickinbotham, Simon Dubey, Rahul Friel, Imelda Colligan, Andrew Price, Mark Tyrrell, Andy M. School of Physics Engineering and Technology University of York Intelligent Systems & Robotics Research Group United Kingdom Missouri State University Computer Science United States School of Mechanical & Aerospace Engineering Queen's University Belfast United Kingdom

ISBN: (纸本)9798350308365

For a long time engineering design has relied on human engineers manually crafting and refining designs using their expertise and experience. In Bio-inspired Evolutionary Development (EvoDevo), generative algorithms are employed to investigate a broader design space that may go beyond what human engineers have considered. Previous literature has demonstrated the use of quality and diversity (QD) algorithms in evolutionary approaches to drive the process to better quality solutions. This paper provides a study to understand the effects of using QD algorithms in EvoDevo processes for engineering design. This paper also analyses the impact of using different behavioural characterisations (BC) in the performance of the quality of the solutions found. The results demonstrate that quality and diversity algorithms can find better solutions than other EAs for engineering design problems. It was also found that the characterisation of the BC is important to get the best results. © 2024 IEEE.

关键词： evodevo generative design neural networks quality diversity structural engineering

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Mapping of large scale fluid power system simulations on a distributed memory parallel computer using genetic algorithms

Mapping of large scale fluid power system simulations on a d...

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ASME 1996 international Mechanical engineering congress and Exposition, IMECE 1996

作者： Pollmeier, K. Burrows, C.R. Edge, K.A. Fluid Power Centre School of Mechanical Engineering University of Bath Bath United Kingdom

ISBN: (纸本)9780791815342

Parallel simulation of fluid power systems using the transmission-line modeling method of fers the benefit of increased speed of execution, but requires the system model to be partitioned on to individual processors [Burton, 1994], In this paper we address the automatic placement of component models on processors of a distributed memory parallel machine. A genetic algorithm is used to map the different processes onto several processors. The objective is to minimise the total processing time in order to achieve real time performance. For fine grained computation problems the communication time cannot be neglected, i.e. we consider the computation and the communication time of each task. This mapping problem is a combinatorial optimization problem which can be reduced to the graph partitioning problem which is shown to be NP-complete. Combining genetic algorithms with heuristics leads to optimal or very good sub-optimal solutions. A hydraulic example circuit is partitioned in four and eight subsystems, respectively, and the simulation is implemented on a Transputer based platform. Using eight processors a speed up of 3.7 was achieved. © 1996 American Society of Mechanical Engineers (ASME). All rights reserved.

关键词： Genetic algorithms

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Revisiting approximation techniques to reduce order of interval system

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IFAC-PapersOnLine 2016年第1期49卷 241-246页

作者： Choudhary, Amit Kumar Nagar, Shyam Krishna Department of Electrical Engineering Indian Institute of Technology Banaras Hindu University Varanasi Varanasi U.P.221005 India

Large interconnected modules result in complex system of higher order and often of interval structure, making the overall study and analysis, time consuming and complicated. Accepting the challenge to state an approximate model of such system, both system analysts and control engineers, headed towards the model order reduction. Continuing the same, this paper revisits few noteworthy estimation techniques for simplification of discrete-time interval system. In particular, denominator is derived through reciprocal algorithm and numerator by two varied algorithms. The proposed algorithms are validated with examples from literatures and real-time test systems via assessment of error computation. Limitation encountered during the course is also taken into count. © 2016, IFAC (international Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Real time systems Approximation theory Bilinear transformation Direct truncation Discrete time intervals Mixed approach Order reduction Pade approximation Routh approximation

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A modified quantum-based particle swarm optimization for engineering inverse problem

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COMPEL-THE international JOURNAL FOR computation AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC engineering 2017年第1期36卷 168-187页

作者： Rehman, Obaid Ur Yang, Shiyou Khan, Shafi Ullah Zhejiang Univ Dept Elect Engn Hangzhou Zhejiang Peoples R China

Purpose - The purpose of this paper is to explore the potential of standard quantum-based particle swarm optimization (QPSO) methods for solving electromagnetic inverse problems. Design/methodology/approach - A modified QPSO algorithm is designed. Findings - The modified QPSO algorithm is an efficient and robust global optimizer for optimizing electromagnetic inverse problems. More specially, the experimental results as reported on different case studies demonstrate that the proposed method can find better final optimal solution at an early stage of the iterating process (uses less iterations) as compared to other tested optimal algorithms. Originality/value - The modifications include the design of a new position updating formula, the introduction of a new mutation strategy and a dynamic control parameter to intensify the convergence speed of the algorithm.

关键词： Inverse problem Particle swarm optimization Global optimization Quantum mechanics

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Optimization Design Model of Functional Gradient Thermal Barrier Coating Material by Using Parallel computation

Optimization Design Model of Functional Gradient Thermal Bar...

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international Symposium on Materials Application and engineering (SMAE)

作者： Chen, Zhao Zhang, Shesheng Wuhan Univ Technol Wuhan 430063 Peoples R China

It is important for huge ship to find the ceramic/metal functional gradient thermal barrier coating materials. A parallel computation model is built for optimization design of three-dimensional ceramic/metal functionally gradient thermal barrier coating material. According to the control equation and initial-boundary conditions, the heat transfer problem is considered, and numerical algorithms of optimization design is constructed by adapting difference method. The numerical results shows that gradient thermal barrier coating material can improve the function of material.

关键词： Numerical methods

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Locality of computation for Stencil Optimization 16th

Locality of Computation for Stencil Optimization

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16th international Conference on algorithms and Architectures for Parallel Processing (ICA3PP)

作者： Yuan, Lufeng Liu, Junhong Luo, Yulong Tan, Guangming Chinese Acad Sci Inst Comp Technol State Key Lab Comp Architecture Beijing Peoples R China

ISBN: (纸本)9783319495835;9783319495828

Stencil computation is a performance critical kernel that is widely used in scientific and engineering applications. In this paper we develop a redundant computation elimination (RCE) algorithm to exploit temporal locality. We implement the RCE optimization strategy using ROSE compiler infrastructure. The experiments with a benchmark of eleven stencil applications show that temporal locality of RCE averagely improves performance by 15.4% and 10.1% for benchmark without or with SIMD optimization.

关键词： Optimization computation locality Stencil

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AN ACCELERATION TECHNIQUE FOR THE computation OF PARTICIPATING RADIATIVE HEAT TRANSFER

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ASME international Mechanical engineering congress and Exposition

作者： Mathur, Sanjay R. Murthy, Jayathi Y. Purdue Univ Sch Mech Engn W Lafayette IN 47907 USA

ISBN: (纸本)9780791843826

It is known that the finite volume and discrete ordinates methods for computing participating radiation are slow to converge when the optical thickness of the medium becomes large. This is a result of the sequential solution procedure usually employed to solve the directional intensities, which couples the ordinate directions and the energy equation loosely. Previously published acceleration techniques have sought to employ a governing equation for the angular-average of the radiation intensity to promote inter-directional coupling. These techniques have not always been successful, and even where successful, have been found to destroy the conservation properties of the radiative transfer equation. In this paper, we develop an algorithm called Multigrid Acceleration using Global Intensity Correction (MAGIC) which employs a multigrid solution of the average intensity and energy equations to significantly accelerate convergence, while ensuring that the conservative property of the radiative transfer equation is preserved. The method is shown to perform well for radiation heat transfer problems in absorbing, emitting and scattering media, both and without radiative equilibrium, and across a range of optical thicknesses.

关键词： Radiation (Physics) algorithms Radiative heat transfer Scattering (Physics) computation Electromagnetic scattering Heat transfer Equilibrium (Physics) Radiation scattering

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COUPLING OF MICRO-SCALE AND MACRO-SCALE EULERIAN-LAGRANGIAN MODELS FOR THE computation OF SHOCKED PARTICLE-LADEN FLOWS

COUPLING OF MICRO-SCALE AND MACRO-SCALE EULERIAN-LAGRANGIAN ...

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ASME international Mechanical engineering congress and Exposition (IMECE2013)

作者： Davis, Sean Sen, Oishik Jacobs, Gustaaf Udaykumar, H. S. San Diego State Univ Aerosp Engn San Diego CA 92115 USA Univ Iowa Mech & Ind Engn Iowa City IA 52242 USA

ISBN: (纸本)9780791856314

The accuracy and efficiency of several algorithms that couple output from full resolution micro-scale Direct Numerical Simulation computations to input for macro-scale Eulerian-Lagrangian (EL) methods for the computation of high-speed, particle-laden flow are assessed. A Stochastic Collocation method, a Gaussian Radial Basis Function (RBF) Artificial Neural Network (ANN), and an improved RBF-ANN are compared for the fitting of an analytical drag coefficient formula that depends on Mach number and Reynolds number The improved RBF-ANN uses a clustering algorithm to enhance conditioning of interpolation matrices. The fitted drag coefficient mantle, used to trace point particles in macro-scale computations, is in excellent agreement with the analytical drag formula. The SC method requires fewer micro-scale realizations to obtain comparable accuracy of the drag coefficient. The Gaussian RBF does not converge monotonically, while the improved RBF-ANN converges algebraically and has the potential to provide error estimates.

关键词： Stochastic systems

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