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IEEE MTT-S international Conference on Numerical Electromagnetic and Multiphysics Modeling and optimization (NEMO)

作者： Yazar, Sirin Hatipoglu, M. Enes Eris, Ozgur Ergul, Ozgur Dikmen, Fatih Middle East Tech Univ Dept Elect & Elect Engn TR-06800 Ankara Turkiye Gebze Tech Univ Elect Engn Dept TR-41400 Gebze Kocaeli Turkiye ASELSAN Res Ctr TR-06200 Ankara Turkiye

ISBN: (纸本)9798350347401

Well-designed arrangements of arrays of circular lossy dielectric rods with finite lengths have been exploited to obtain proper radiation patterns for microwave applications. Accelerated three-dimensional (3D) numerical modeling of such radiation mechanisms via the multilevel fast multipole algorithm (MLFMA) is suitable for well-matched results with real-life experiments. Enabling rigorous and accurate analyses of the corresponding problems, MLFMA, has been observed to provide quasi-optimal designs within a reasonable period of time, when this algorithm is efficiently combined with genetic algorithms (GAs). However, as shown in this contribution, the corresponding two-dimensional (2D) multiple scattering modeling via a well-conditioned version of the T-matrix method provides a much faster tool for GAs to optimize radiation patterns for a goal set on the central cross section plane of the rod arrays. Optimized geometries obtained using a combination of the 2D solver and GAs have been validated by using a 3D solver based on MLFMA to demonstrate the feasibility of the approach.

关键词： Genetic algorithms T-matrix method multilevel fast multipole algorithm microwave applications

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A novel approach to Bilevel nonlinear programming

A novel approach to Bilevel nonlinear programming

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international workshop on multilevel optimization - algorithms and applications

作者： Tuy, H. Migdalas, A. Hoai-Phuong, N. T. Inst Math Hanoi 10000 Vietnam Tech Univ Crete Khania Greece

Recently developed methods of monotonic optimization have been applied successfully for studying a wide class of nonconvex optimization problems, that includes, among others, generalized polynomial programming, generalized multiplicative and fractional programming, discrete programming, optimization over the efficient set, complementarity problems. In the present paper the monotonic approach is extended to the General Bilevel Programming GBP Problem. It is shown that (GBP) can be transformed into a monotonic optimization problem which can then be solved by "polyblock" approximation or, more efficiently, by a branch-reduce-and-bound method using monotonicity cuts. The method is particularly suitable for Bilevel Convex Programming and Bilevel Linear Programming.

关键词： bilevel nonlinear programming bilevel convex programming bilevel linear programming leader and follower game monotonic optimization polyblock approximation branch-reduce-and-bound method monotonicity cuts

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A new multilevel inverter with genetic algorithm optimization for hybrid power station application 4

A new multilevel inverter with genetic algorithm optimizatio...

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4th international Conference on optimization and applications, ICOA 2018

作者： Eddine, Khalili Taj Abdelhadi, Raihani Omar, Bouattane Hassan, Ouajji SSDIA Lab ENSET Mohammedia Hassan II University Casablanca Morocco

ISBN: (纸本)9781538642252

multilevel inverters are one of the most brilliant technology evolution in power conversion. It provides a stair wave output signal out of multi DC sources used as input. This paper presents a new multilevel inverter topology. The 7 levels architecture principle used in this study is first presented. In order to achieve a better signal output quality an adaptive genetic algorithm is used to reduce the harmonic content. The THD minimization is realized by calculating the appropriate switching angle in real time. However this study is focused on the 7 levels case, it also refers to other levels. The analysis is based on THD evaluation in different cases. All simulations and programming were done using Matlab. © 2018 IEEE.

关键词： Genetic algorithms

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Evolutionary algorithms in aircraft trim optimization

Evolutionary algorithms in aircraft trim optimization

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19th international Conference on Database and Expert Systems applications

作者： Tupy, Jaroslav Zelinka, Ivan Tomas Bata Univ Zlin Dept Appl Informat Zlin 76005 Czech Republic

ISBN: (纸本)9780769532998

In this paper, the calculation of aircraft trimming process is presented in a sufficiently understandable way using a unique combination of global optimization theory and the direct hand-on computer simulation. The methods of artificial intelligence and heuristic algorithms handling with the equations of airplane motion are presented in this paper. The main aim was to use them for trimming the flying aircraft to the steady state flight upon setting the flight conditions of various kinds. New approach of SOMA (Self Organizing Migrating Algorithm) has been used here to find the vehicle equilibrium state. The method can be practically utilized in construction of airplanes as well as the flight simulators design.

关键词： Heuristic methods

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A methodology for comparing optimization algorithms for auto-tuning

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FUTURE GENERATION COMPUTER SYSTEMS-THE international JOURNAL OF ESCIENCE 2024年 159卷 489-504页

作者： Willemsen, Floris-Jan Schoonhoven, Richard Filipovic, Jiri Torring, Jacob O. van Nieuwpoort, Rob van Werkhoven, Ben Leiden Univ Niels Bohrweg 1 NL-2333 CA Leiden Netherlands Netherlands eSci Ctr Sci Pk 402 NL-1098 XH Amsterdam Netherlands Ctr Wiskunde & Informat Sci Pk 123 NL-1098 XG Amsterdam Netherlands Masaryk Univ Inst Comp Sci Sumavska 416-15 Brno 60200 Czech Republic Norwegian Univ Sci & Technol Hogskoleringen 1 N-7034 Trondheim Norway

Adapting applications to optimally utilize available hardware is no mean feat: the plethora of choices for optimization techniques are infeasible to maximize manually. To this end, auto -tuning frameworks are used to automate this task, which in turn use optimization algorithms to efficiently search the vast searchspaces. However, there is a lack of comparability in studies presenting advances in auto -tuning frameworks and the optimization algorithms incorporated. As each publication varies in the way experiments are conducted, metrics used, and results reported, comparing the performance of optimization algorithms among publications is infeasible. The auto -tuning community identified this as a key challenge at the 2022 Lorentz Center workshop on auto -tuning. The examination of the current state of the practice in this paper further underlines this. We propose a community -driven methodology composed of four steps regarding experimental setup, tuning budget, dealing with stochasticity, and quantifying performance. This methodology builds upon similar methodologies in other fields while taking into account the constraints and specific characteristics of the auto -tuning field, resulting in novel techniques. The methodology is demonstrated in a simple case study that compares the performance of several optimization algorithms used to auto -tune CUDA kernels on a set of modern GPUs. We provide a software tool to make the application of the methodology easy for authors, and simplifies reproducibility of results.

关键词： Auto-tuning Methodology optimization algorithms Performance optimization Performance comparison

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Implemental techniques and their effectives for evolutionary algorithms used to solve multilevel lot sizing problems

Implemental techniques and their effectives for evolutionary...

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2010 IEEE 5th international Conference on Bio-Inspired Computing: Theories and applications, BIC-TA 2010

作者： Kaku, Ikou Xiao, Yiyong Department of Management Science and Engineering Akita Prefectural University Tutiya-Ebinokuti 84-4 Yulihonjo 015-0055 Japan Department of Engineering and System Engineering Beihang University Beijing 100191 China

ISBN: (纸本)9781424464388

multilevel lot siZing (MLLS) problem is a combinational optimization problem which has been proved NP-hard without restrictive assumption on the product structure. Several evolutionary algorithms were developed to solve the MLLS problem in literature, such as genetic algorithm, simulated annealing, swarm particle optimization, soft optimization based on segmentation, ant colony optimization, variable neighbourhood search and so on. In this paper we investigate implemental techniques and their effectives for those evolutionary algorithms used to solve the MLLS problem. Obtained results can be used to specify the characteristics of the solution of the MLLS problems and to help developing more efficient evolutionary algorithms. © 2010 IEEE.

关键词： Ant colony optimization

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OptorSim: A grid simulator for studying dynamic data replication strategies

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international JOURNAL OF HIGH PERFORMANCE COMPUTING applications 2003年第4期17卷 403-416页

作者： Bell, WH Cameron, DG Capozza, L Millar, AP Stockinger, K Zini, F Univ Glasgow Particle Phys Grp Glasgow G12 8QQ Lanark Scotland Univ Glasgow Expt Particle Phys Grp Glasgow G12 8QQ Lanark Scotland Johannes Gutenberg Univ Mainz Inst Kernphys A4 D-55099 Mainz Germany CERN European Org Nucl Res CH-1211 Geneva Switzerland IRST ITC I-38050 Povo Trento Italy

Computational grids process large, computationally intensive problems on small data sets. In contrast, data grids process large computational problems that in turn require evaluating, mining and producing large amounts of data. Replication, creating geographically disparate identical copies of data, is regarded as one of the major optimization techniques for reducing data access costs. In this paper, several replication algorithms are discussed. These algorithms were studied using the Grid simulator: OptorSim. OptorSim provides a modular framework within which optimization strategies can be studied under different Grid configurations. The goal is to explore the stability and transient behaviour of selected optimization techniques. We detail the design and implementation of OptorSim and analyze various replication algorithms based on different Grid workloads.

关键词： grid computing replica optimization simulation

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Analysis of Optimum THD in Asymmetrical H-Bridge multilevel Inverter Using HPSO Algorithm 2nd

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2nd international Conference on Intelligent Computing and applications (ICICA)

作者： Dhanalakshmi, M. Ammal Ganesh, M. Parani Paul, Keerthana KCG Coll Technol Dept EEE Madras Tamil Nadu India

ISBN: (纸本)9789811016455;9789811016448

This paper analyses an optimum Total Harmonic Distortion (THD) value for multilevel inverters using Hybrid Particle Swarm optimization Algorithm (HPSO). The proposed paper instigates an algorithm which supersedes the conventional algorithms in finding out an optimum global value. The prime objective of this paper is to reduce the THD value of the Asymmetric H-bridge multilevel inverters by choosing appropriate values from the inequality constraints. The proposed algorithm is simulated for an 11-level H bridge inverter using matlab 2014 version software. The results interpreted seemed to have a satisfactory higher order harmonic elimination compared to the conventional methods.

关键词： Total harmonic distortion (THD) Asymmetrical H-bridge multilevel inverter Hybrid particle swarm optimization algorithm (HPSO)

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Antenna Selection for MIMO Systems Using Biogeography Based optimization

Antenna Selection for MIMO Systems Using Biogeography Based ...

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international workshop on Antenna Technology - Small Antennas, Innovative Structures, and applications (iWAT)

作者： Fountoukidis, Konstantinos C. Siakavara, Katherine Goudos, Sotirios K. Kalialakis, Christos Aristotle Univ Thessaloniki Dept Phys Thessaloniki Greece CTTC Microwave Syst & Nanotechnol Dept Castelldefels Spain

ISBN: (纸本)9781509051779

In this work, we solve a problem of antenna selection (AS) for a multiple-input multiple-output (MIMO) system under the constraint of the channel capacity maximization. The biogeography-based optimization (BBO) algorithm is applied on the joint transmitter and receiver AS for the channel capacity function. We apply different BBO migration models for simulated channels. The comparisons with other popular evolutionary algorithms such as the genetic algorithm (GA) and the ant colony optimization (ACO) show the efficiency and the applicability of the BBO algorithm. Results are given for three representative scenarios involving selection of 2x4, 3x5, 4x6 antennas in a 16x16 MIMO system.

关键词： Multiple-input multiple-output (MIMO) systems antenna selection (AS) biogeography-based optimization (BBO) genetic algorithm (GA) ant colony optimization (ACO) evolutionary algorithms (EA

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Mesh partitioning: A multilevel ant-colony-optimization algorithm

Mesh partitioning: A multilevel ant-colony-optimization algo...

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international Parallel and Distributed Processing Symposium, IPDPS 2003

作者： Korošec, Peter Šilc, Jurij Robič, Borut Computer Systems Department Jožef Stefan Institute Jamova 39 LjubljanaSI-1000 Slovenia Faculty of Computer and Information Science University of Ljubljana Tržaška 25 LjubljanaSI-1000 Slovenia

ISBN: (纸本)0769519261

Mesh partitioning is an important problem that has extensive applications in many areas. multilevel algorithms are a successful class of optimization techniques which address the mesh partitioning problem. In this paper we present an enhancement of the technique that uses a nature inspired metaheuristic to achieve higher quality partitions. We apply and study a multilevel ant-colony (MACO) optimization, which is a relatively new metaheuristic search technique for solving optimization problems. The MACO algorithm performed very well and is superior to the classical k-METIS and Chaco algorithms. Furthermore, it is even comparable to the combined evolutionary/multilevel scheme used in the JOSTLE evolutionary algorithm. Our MACO algorithm returned also some solutions that are better than currently available solutions in the graph partitioning archive. © 2003 IEEE.

关键词： Ant colony optimization

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