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conference on Active and Passive Smart Structures and Integrated Systems XII

作者： Cai, Wen Harne, Ryan L. Ohio State Univ Dept Mech & Aerosp Engn Columbus OH 43210 USA

ISBN: (数字)9781510625907

ISBN: (纸本)9781510625891;9781510625907

Energy harvesters with wide frequency range, long lifetime, and high output power are preferred to serve as power supplies for wireless devices. Motivated to guide the design of a robust energy harvesting platform, an analytical model based on the Euler-Bernoulli beam theory for a laminated beam is first presented to predict the nonlinear response of the system when subjected to harmonic base acceleration and tunable magnetic forces. Following experimental validation, a multi-objective optimization based on a genetic algorithm considers how to improve the frequency range of high performance, decrease peak strain level, and maximize output power by manipulating the design of the nonlinear energy harvester. The optimization results indicate that a slightly monostable configuration is superior when taking all three aspects into consideration.

关键词： optimization (mathematics) Analytical research Copper Energy harvesting Genetic algorithms Beam shaping Complex systems Magnetism Power supplies Electrodes

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Traffic-Aware Application Mapping for Network-on-Chip based Multiprocessor System-on-Chip 17

Traffic-Aware Application Mapping for Network-on-Chip based ...

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2015 IEEE 17th International conference on high performance Computing and Communications (HPCC)

作者： Yang, Lei Liu, Weichen Jiang, Weiwen Zhang, Wei Li, Mengquan Yi, Juan Liu, Duo Sha, Edwin H. -M. Chongqing Univ Coll Comp Sci Chongqing Peoples R China Hong Kong Univ Sci & Technol Dept Elect & Comp Engn Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781479989379

Network on Chip (NoC) has become a promising solution for the communication paradigm of the next-generation multiprocessor system-on-chip (MPSoC). As communication has become an integral part of on-chip computing, researchers are paying more attention to its implementation and optimization. Traditional techniques that model inter-processor communication inaccurately will lead to unexpected runtime performance, which is on average 90.8% worse than the predicted results based on an observation. In this paper, we present an application mapping and scheduling technique for NoC-based MPSoCs that integrates fine-grain optimization on inter-processor communications with the objective of minimizing the schedule length. A communication model is proposed to address properly the latency of inter-processor communication with network contention. performance evaluation results show that solutions obtained by the proposed technique can generate realistic performance that is on average 34.7% higher than traditional techniques, and the Integer-Linear Programming (ILP) based approach can outperform the state-of-the-art heuristic algorithms by 31.1%. A case study on H.264 HDTV decoder shows that our approach achieves 22.8% improvement in prediction accuracy, 20.9% improvement in performance and 40% reduction in the number of network contentions.

关键词： Network-on-Chip Mapping Scheduling Communication optimization

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nonlinear Weighted Multiple Centrality Corrections Interior Point Method for Optimal Power Flow

Nonlinear Weighted Multiple Centrality Corrections Interior ...

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International conference on Sustainable Power Generation and Supply

作者： Huang, Zhiguang Jiang, Quanyuan Zhejiang Univ Coll Elect Engn Hangzhou 310027 Zhejiang Peoples R China

ISBN: (纸本)9781424449347

Optimal power flow (OPF) is a large scale nonlinear non-convex optimization problem. In the last decades many algorithms are developed to solve these problems and the interior point method (IPM) is a popular one. The primal-dual IPMs and their later developments have attracted much research interest. Impressed by the improvements in convergent performance of the further developed multiple centrality corrections IPM in linear programming (LP), this paper extended it to nonlinear programming and made certain modifications to make it adaptable to the nonlinear OPF. Test results on several cases ranging from 9-bus to 2796-bus system indicate the efficiency and high convergence of the proposed algorithm, which outperforms the original multiple centrality corrections IPM. Comparisons between the proposed method and other forms of interior point methods are also given to show its advantage in convergent performance.

关键词： interior point method weighted multiple centrality corrections optimal power flow power system

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The Large-Scale optimization Problem of Product Distribution in Orders

The Large-Scale Optimization Problem of Product Distribution...

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International conference on Applied Mathematics and Computational Science (ICAMCS.NET)

作者： Semenkina, Olga Ryzhikov, Ivan Semenkin, Eugene Joint Stock Co Nonferrous Met Plant Krastsvetmet Numer Modeling Off Krasnoyarsk Russia Reshetnev Siberian State Univ Sci & Technol Syst Anal & Control Dept Krasnoyarsk Russia

ISBN: (纸本)9781538694688

In this paper, we consider a large-scale global optimization problem, which takes place in distribution of large number of products into individual orders. In general, the amount of each product is limited and the packaging is constrained, which means that the initial problems can be reduced to constrained nonlinear optimization problem. The high dimensionality and complexity of this problem leads to developing of the specific problem-oriented optimization tool. Two different approaches of solving this problem were considered. The first one is based on the reduction of the initial problem to the discrete optimization problem with dimension is equal to the product of orders number and number of products. The second approach is based on the decomposition of the initial problem into two related problems: combinatorial problem of ranking orders and combinatorial/discrete optimization problem of optimal distributing. As the main extremum seeking approaches, the evolution based and nature-inspired algorithms were used and modified for efficiently solving the considered problem. We also propose the set of particular problems: different combinations of orders and products, which were used for the algorithms' parameters tuning. In addition, the proposed reduction approaches and related algorithms were compared in its performance on these particular problems.

关键词： constrained knapsack problem combinatorial optimization problem hierarchical optimization evolution-based algorithms decision-making support system

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The method of navigation performance optimization analysis for high speed monohull ships 2

The method of navigation performance optimization analysis f...

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2022 2nd International conference on Mechanical Automation and Electronic Information Engineering, MAEIE 2022

作者： Yang, Zhaolong Zou, Zaojian Wang, Xuegang School of Naval Architecture Ocean and Civil Engineering Shanghai Jiao Tong University Shanghai200240 China CCCC Fourth Harbor Engineering Institute Co. Ltd. Guangzhou510230 China

This paper is based on the drag resistance test data of the high-speed monohull model, a mathematical model for comprehensive optimization of the navigation performance of a high-speed monohull taking into account the rapidity, maneuverability, seakeeping and static performance of the ship is constructed. The optimization calculation software based on particle swarm, standard genetic algorithm and growth mechanism genetic algorithm is designed and written. Taking a high-speed monolithic sea-going ship with a displacement of 1500 tons and a large inclination-measuring single propeller as the object of discussion, the comparison of optimization methods, the comprehensive navigation performance of different ship types and the sensitivity analysis of design variables are carried out respectively. It provides a practical approach and an effective and practical scientific method for analysis and evaluation of how to maintain the comprehensive optimal navigation performance of high-speed monohull ships. At the same time, it provides a way to quickly evaluate the comprehensive performance of similar high-speed monolithic ships in the preliminary design stage, and can also obtain the model diagram with the best comprehensive performance through this software or method, which is useful for shortening the preliminary design cycle of the ship and improving the design quality of the ship. It has important reference value. © Published under licence by IOP Publishing Ltd.

关键词： Genetic algorithms

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Affine Takagi-Sugeno fuzzy model identification based on a novel fuzzy c-regression model clustering and particle swarm optimization

Affine Takagi-Sugeno fuzzy model identification based on a n...

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16th IEEE Mediterranean Electrotechnical conference (MELECON)

作者： Soltani, Moez Bessaoudi, Talel Chaari, Abdelkader BenHmida, Faycal High Sch Sci & Tech Tunis Ave Taha HusseinBP 56 Tunis 1008 Tunisia Bab Menara Tunis 1008 Tunisia

ISBN: (纸本)9781467307840

In this paper, a novel Takagi-Sugeno fuzzy model identification based on a new fuzzy c-regression model clustering algorithm and particle swarm optimization is presented. The main motivation for this work is to develop an identification procedure for nonlinear systems taking into account the noise. In addition, a new distance is used in the objective function of the FCRM algorithm, replacing the one used in this type of algorithm. Thereafter, particle swarm optimization is employed to fine tune parameters of the obtained fuzzy model. The performance of the proposed approach is validated by studying the nonlinear plant modeling problem.

关键词： Clustering algorithms

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An interval-matrix branch-and-bound algorithm for bounding eigenvalues

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optimization METHODS & software 2017年第4期32卷 872-891页

作者： Nerantzis, Dimitrios Adjiman, Claire S. Imperial Coll London Dept Chem Engn Ctr Proc Syst Engn South Kensington Campus London SW7 2AZ England

We present and explore the behaviour of a branch-and-bound algorithm for calculating valid bounds on the kth largest eigenvalue of a symmetric interval matrix. Branching on the interval elements of the matrix takes place in conjunction with the application of Rohn's method (an interval extension of Weyl's theorem) in order to obtain valid outer bounds on the eigenvalues. Inner bounds are obtained with the use of two local search methods. The algorithm has the theoretical property that it provides bounds to any arbitrary precision (assuming infinite precision arithmetic) within finite time. In contrast with existing methods, bounds for each individual eigenvalue can be obtained even if its range overlaps with the ranges of other eigenvalues. performance analysis is carried out through nine examples. In the first example, a comparison of the efficiency of the two local search methods is reported using 4000 randomly generated matrices. The eigenvalue bounding algorithm is then applied to five randomly generated matrices with overlapping eigenvalue ranges. Valid and sharp bounds are indeed identified given a sufficient number of iterations. Furthermore, most of the range reduction takes place in the first few steps of the algorithm so that significant benefits can be derived without full convergence. Finally, in the last three examples, the potential of the algorithm for use in algorithms to identify index-1 saddle points of nonlinear functions is demonstrated.

关键词： global optimization branch-and-bound interval matrix eigenvalue bounds index-1 saddle points

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PSO Algorithm with Decreasing Inertia Weights Based on Sigmoid Function 2

PSO Algorithm with Decreasing Inertia Weights Based on Sigmo...

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2nd International conference on Algorithm, Image Processing and Machine Vision, AIPMV 2024

作者： Tian, Weiye Zhu, Jianxiao Cheng, Wei Bao, Jiandong Nanjing University of Science and Technology Nanjing China Konig Electronic Technology Co. Ltd Suzhou China

ISBN: (纸本)9798350390254

The traditional particle swarm algorithm in solving the optimal value of high-dimensional nonlinear problems will fall into the local optimal value and converge prematurely, and the optimization effect is not good, based on this this paper proposes a multi-strategy improved particle swarm algorithm. The Latin hypercube sampling method is used to initialize the population position, the cosine adjustment learning factor is nonlinear dynamic change, and an inertia weight formula based on sigmoid function with nonlinear dynamic adjustment is constructed. Four classical test functions are selected for simulation experiments, and according to the obtained experimental data and other algorithms are compared and analyzed, the improved algorithm proposed in this paper has a stronger ability to jump out of the local optimum, a higher convergence accuracy, and a better performance of finding the optimum. © 2024 IEEE.

关键词： optimization algorithms

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Sequential Quadratic Programming Algorithm for Real-Time Mixed-Integer nonlinear MPC 60

Sequential Quadratic Programming Algorithm for Real-Time Mix...

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60th IEEE conference on Decision and Control (CDC)

作者： Quirynen, Rien Di Cairano, Stefano Mitsubishi Elect Res Labs Cambridge MA 02139 USA

ISBN: (纸本)9781665436595

nonlinear model predictive control (NMPC) has grown mature and algorithmic techniques exist, e.g., based on sequential quadratic programming (SQP) methods, to handle relatively complex constrained control systems. In addition, model predictive control for hybrid dynamical systems, including both continuous and discrete decision variables, can be implemented efficiently based on state of the art mixed-integer quadratic programming (MIQP) algorithms. This paper proposes a novel mixed-integer SQP (MISQP) optimization algorithm as a heuristic search technique to find feasible, but possibly suboptimal, solutions for real-time implementations of mixed-integer NMPC (MINMPC). Two variants of the MISQP algorithm are described and motivated. Based on a preliminary software implementation, the real-time MISQP performance is illustrated for closed-loop MINMPC simulations on a nontrivial vehicle control case study, featuring worst-case computation times below 30 milliseconds.

关键词： Model predictive control

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Genetic algorithm with Pareto fronts for multi-criteria optimization case study "milling parameters optimization"

Genetic algorithm with Pareto fronts for multi-criteria opti...

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5th International conference on software, Knowledge Information, Industrial Management and Applications, SKIMA 2011

作者： Zeghichi, Nafissa Assas, Mekki Mouss, Leila Hayet Labortory of Automatism and Manufacturing LAP Genie Industrial Department Batna University Batna 05000 Algeria Mechanical Department Laboratory of Engineering Production Batna University Batna 05000 Algeria

ISBN: (纸本)9781467302463

The cutting parameters such as the cutting speed, feed speed, and the chip thickness have huge effects on the machining quality and the productivity rate. The optimal choice of these parameters gives a perfect machining without risks and with high productivity rate. The proposed problem tries to minimizing two nonlinear objectives functions: the machining time and the machining cost under several constraints. The well-chosen of conform optimization methods to resolve this problem gives a quick and reliable decision. The genetic algorithms permit the treatment of non-linear functions. They allow a good exploitation in the field of research as well as the non feasible field is not eliminated but sanctioned with high fitness values and a good exploration by the diversification operations that improve the solution quality. © 2011 IEEE.

关键词： Genetic algorithms

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