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Covariance matrix adapted evolution strategy algorithm-based solution to dynamic economic dispatch problems

ENGINEERING OPTIMIZATION 2009年第7期41卷 635-657页

作者： Manoharan, P. S. Kannan, P. S. Baskar, S. Iruthayarajan, M. Willjuice Dhananjeyan, V. Thiagarajar Coll Engn Dept Elect & Elect Engn Madurai Tamil Nadu India

This article presents a covariance matrix adapted evolution strategy (CMAES) algorithm to solve dynamic economic dispatch (DED) problems. The DED is an extension of the conventional economic dispatch problem, in which optimal settings of generator units are determined with a predicted load demand over a period of time. In this article, the applicability and validity of the CMAES algorithm is demonstrated on three DED test systems with a sequential decomposition approach. The results obtained using the CMAES algorithm are compared with results obtained using the real-coded genetic algorithm, the Nelder-Mead simplex method, and other methods from the literature. To compare the performance of the various algorithms, statistical measures like best, mean, worst, standard deviation, and mean computation time over 20 independent runs are taken. The effect of population size on the performance of the CMAES algorithm is also investigated. The simulation experiments reveal that the CMAES algorithm performs better in terms of fuel cost and solution consistency. Karush-Kuhn-Tucker conditions are applied to the solutions obtained using the CMAES algorithm to verify optimality. It is found that the obtained results satisfy the Karush-Kuhn-Tucker conditions and confirm optimality.

关键词： electrical power systems covariance matrix adapted evolution strategy (CMAES) dynamic economic dispatch penalty-parameter-less scheme real-coded genetic algorithm Karush-Kuhn-Tucker conditions

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Application of the differential-evolution strategy to the design of frequency-selective surfaces

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INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING 2005年第2期15卷 173-180页

作者： Luo, XF Oing, A Lee, CK Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore Natl Univ Singapore Temasek Labs Singapore 117508 Singapore

An optimization approach based on the diffential evolution strategy (DES) is applied to the design of frequency-selective surfaces (FSS). The spectral Galerkin method is used to analyze the electromagnetic scattering from a FSS screen while DES is used to tune the FSS unit-cell dimensions and dielectric properties in order to achieve the prescribed frequency responses. The DES is compared to the real-coded genetic algorithm. The simulated results of FSS dipole arrays are presented, which demonstrate that DES is a more simple, yet more efficient and more robust, method for the design of FSS. (c) 2005 Wiley Periodicals, Inc.

关键词： frequency-selective surfaces differential-evolution strategy spectral Galerkin method dipole array real-coded genetic algorithm

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An efficient genetic algorithm for the design optimization of cold-formed steel portal frame buildings

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STEEL AND COMPOSITE STRUCTURES 2013年第5期15卷 519-538页

作者： Phan, D. T. Lim, J. B. P. Tanyimboh, T. T. Sha, W. Univ Tunku Abdul Rahman Dept Civil Engn Kuala Lumpur 53300 Malaysia Queens Univ Belfast Sch Planning Architecture & Civil Engn Belfast BT9 5AG Antrim North Ireland Univ Strathclyde Dept Civil & Environm Engn Glasgow G4 0NG Lanark Scotland

The design optimization of a cold-formed steel portal frame building is considered in this paper. The proposed genetic algorithm (GA) optimizer considers both topology (i.e., frame spacing and pitch) and cross-sectional sizes of the main structural members as the decision variables. Previous GAs in the literature were characterized by poor convergence, including slow progress, that usually results in excessive computation times and/or frequent failure to achieve an optimal or near-optimal solution. This is the main issue addressed in this paper. In an effort to improve the performance of the conventional GA, a niching strategy is presented that is shown to be an effective means of enhancing the dissimilarity of the solutions in each generation of the GA. Thus, population diversity is maintained and premature convergence is reduced significantly. Through benchmark examples, it is shown that the efficient GA proposed generates optimal solutions more consistently. A parametric study was carried out, and the results included. They show significant variation in the optimal topology in terms of pitch and frame spacing for a range of typical column heights. They also show that the optimized design achieved large savings based on the cost of the main structural elements;the inclusion of knee braces at the eaves yield further savings in cost, that are significant.

关键词： optimization cold-formed steel portal frames niching real-coded genetic algorithm

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genetic algorithm and M-estimator based robust sequential estimation of parameters of nonlinear sinusoidal signals

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COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION 2011年第7期16卷 2796-2809页

作者： Mitra, Sharmishtha Mitra, Amit Kundu, Debasis Indian Inst Technol Dept Math & Stat Kanpur 208016 Uttar Pradesh India

Estimation of parameters of nonlinear superimposed sinusoidal signals is an important problem in digital signal processing. In this paper, we consider the problem of estimation of parameters of real valued sinusoidal signals. We propose a real-coded genetic algorithm based robust sequential estimation procedure for estimation of signal parameters. The proposed sequential method is based on elitist generational genetic algorithm and robust M-estimation techniques. The method is particularly useful when there is a large number of superimposed sinusoidal components present in the observed signal and is robust with respect to presence of outliers in the data and impulsive heavy tail noise distributions. Simulations studies and real life signal analysis are performed to ascertain the performance of the proposed sequential procedure. It is observed that the proposed methods perform better than the usual non-robust methods of estimation. (C) 2010 Elsevier B.V. All rights reserved.

关键词： Elitism Generational genetic algorithm M-estimator Nonlinear least squares Periodogram estimates real-coded genetic algorithm Robust estimation Sequential estimation Speech signals

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A multi-crossover genetic approach to multivariable PID controllers tuning

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EXPERT SYSTEMS WITH APPLICATIONS 2007年第3期33卷 620-626页

作者： Chang, Wei-Der Shu Te Univ Dept Comp & Commun Kaohsiung 824 Taiwan

In this paper, we will propose a modified crossover formula in genetic algorithms (GAs), and use this method to determine PID controller gains for multivariable processes. It is well known that GA is globally optimal search method borrowing the concepts from biological evolutionary theory. In the traditional crossover fashion, only two parent chromosomes are usually used to be crossed by each other. The proposed algorithm, however, is designed to provide a more accurate adjusting direction for evolving offspring because of the use of multi-crossover genetic operations. Then we apply the innovative GA into the design of multivariable PID control systems for deriving optimal or near optimal control gains such that the defined performance criterion of integrated absolute error (IAE) is minimized as much as possible. Finally, a 2 x 2 multivariable controlled plant with strong interactions between input and output pairs will be illustrated to demonstrate the effectiveness of the proposed method. Some comparison results with the traditional GA and BLT method are also demonstrated in the simulation. (c) 2006 Elsevier Ltd. All rights reserved.

关键词： PID control multivariable processes real-coded genetic algorithm multiple crossover

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Inferring the distribution of norovirus in individual oysters below the limit of quantification by pooled sampling

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RISK ANALYSIS 2024年第5期44卷 1183-1192页

作者： Wang, Jianxin Zhou, Chen Wang, Yeru Beijing Forestry Univ Sch Informat Beijing Peoples R China China Natl Ctr Food Safety Risk Assessment Risk Assessment Div 1 Beijing Peoples R China

Norovirus (NoV) in oysters is a food safety risk of much concern. In order to assess the risk of the exposure, the distribution of the number of NoV copies contained in each oyster should be acquired first for comprehensively quantifying the associated risks. However, the part of the distribution below the limit of quantification cannot be obtained directly by laboratory detecting methods, which hampers accurate assessment. To tackle this challenging problem, a systematic method (Distribution Inference Method by Pooled Sampling) is proposed to infer the unobservable part of distribution based upon all measurements of the pooled samples with n = 2. Using convolutional integrals and real-coded genetic algorithm for inferring, this method has neither requirements for the type or properties of the original distribution, nor requirements for historical data, even nor requirements for the relationship between observable and unobservable parts of the distribution. A series of experiments were conducted on simulated datasets of a variety of types, including normal distribution, uniform distribution, gamma distribution, lognormal distribution, zero-inflated Poisson distribution, their combinations, and even their splicing, covering common distribution types in oyster NoV scenario and more general scenarios. The results show that almost all inferred simulation data and their original counterparts passed Kolmogorov-Smirnov tests, which implies that they are essential of the same distribution. Based on this method, a ready-to-use web system was developed for researchers to infer their original distribution with pooled-sampling measurements from the detection of NoV or even other substances.

关键词： convolutional integral distribution inferring limit of detection limit of quantification norovirus real-coded genetic algorithm

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Optimal design and control of CPU heat sink processes

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IEEE TRANSACTIONS ON COMPONENTS AND PACKAGING TECHNOLOGIES 2008年第1期31卷 184-195页

作者： Chen, Chyi-Tsong Wu, Ching-Kuo Hwang, Chyi Feng Chia Univ Dept Chem Engn Taichung 407 Taiwan Solar Appl Mat Technol Corp Tainan 709 Taiwan I Shou Univ Dept Chem Engn Kaohsiung 804 Taiwan

This paper considers the optimal plate fin design and control for central processing unit (CPU) heat sink processes. First, we apply a finite element method to investigate the heat transfer phenomena of a heat sink process. To have a better heat dispersion performance, a real-coded genetic algorithm is then utilized to search for an optimal set of plate-fin shape parameters. The objective function to be minimized is the entropy generation rate which can take simultaneously the two major factors, heat transfer rate and air resistance, into consideration in the design. The present optimization scheme is able to achieve a better design for heat dispersion than existing methods. To attenuate environmental and time-varying disturbances, a direct adaptive control scheme is then developed for the CPU heat sink process. It is based on using a bounded single neuron controller (SNC) along with a parameter tuning algorithm to regulate the temperature of a selected control point. Extensive comparisons of the SNC-based control performance with the on-off control as well as a PI controller show that the proposed scheme provides excellent control performance despite the existence of unexpected process uncertainties.

关键词： heat sink process optimal design and control parameter tuning algorithm partial differential equation system real-coded genetic algorithm single neuron controller (SNC)

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Multi-modal distribution crossover method based on two crossing segments bounded by selected parents applied to multi-objective design optimization

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JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY 2015年第4期29卷 1443-1448页

作者： Ariyarit, Atthaphon Kanazaki, Masahiro Tokyo Metropolitan Univ Grad Sch Syst Design Dept Aerosp Engn Hino Tokyo 1910065 Japan

This paper discusses airfoil design optimization using a genetic algorithm (GA) with multi-modal distribution crossover (MMDX). The proposed crossover method creates four segments from four parents, of which two segments are bounded by selected parents and two segments are bounded by one parent and another segment. After these segments are defined, four offsprings are generated. This study applied the proposed optimization to a real-world, multi-objective airfoil design problem using class-shape function transformation parameterization, which is an airfoil representation that uses polynomial function, to investigate the effectiveness of this algorithm. The results are compared with the results of the blend crossover (BLX) and unimodal normal distribution crossover (UNDX) algorithms. The objective of these airfoil design problems is to successfully find the optimal design. The outcome of using this algorithm is superior to that of the BLX and UNDX crossover methods because the proposed method can maintain higher diversity than the BLX and UNDX methods. This advantage is desirable for real-world problems.

关键词： Multi-objective optimization real-coded genetic algorithm Crossover method Airfoil design

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Optimal design of minimum multiplier lattice wave digital lowpass filter using metaheuristic techniques

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IET SIGNAL PROCESSING 2018年第6期12卷 700-712页

作者： Barsainya, Richa Aggarwal, Apoorva Rawat, Tarun Kumar Amity Sch Engn & Technol Dept Elect & Commun Engn New Delhi 110061 India Bharati Vidyapeeths Coll Engn Dept Elect & Elect Engn New Delhi 110063 India Netaji Subhas Inst Technol Dept Elect & Commun Engn New Delhi 110078 India

This study aims towards the efficient design of arbitrary-band and halfband lowpass (LP) filter based on lattice wave digital filter (LWDF) structure with the usage of minimal number of multipliers in its structural realisation. The designing of the LP filter is formulated as an optimisation problem where coefficients of LWDF transfer function are iteratively optimised by the evolutionary algorithms. The potential of four optimisation algorithms, real-coded genetic algorithm, particle swarm optimisation, differential evolution algorithm, and cuckoo search algorithm, are explored for determining the optimal LWDF coefficients by minimising the error objective function. The structural realisation of LP using LWDF structure enhances the design accuracy as the usage of multiplier prominently reduces. The simulation and statistical results of the proposed lattice wave digital lowpass filter (LWDLF) and bireciprocal lattice wave digital lowpass filter (BLWDLF) design show significant improvement in the mean square error, passband ripples, transition bandwidth, stopband attenuation, rate of convergence, and execution time. To manifest the efficient design of the proposed LWDLF and BLWDLF, the results are compared with the designed arbitrary-band, halfband canonic-LP filters and previous published works.

关键词： low-pass filters genetic algorithms particle swarm optimisation search problems digital filters minimum multiplier lattice wave digital lowpass filter halfband lowpass filter arbitrary-band lowpass filter optimisation problem real-coded genetic algorithm particle swarm optimisation differential evolution algorithm cuckoo search algorithm LWDLF BLWDLF

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An evolutionary approach for solving the multimodal inverse kinematics problem of industrial robots

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MECHANISM AND MACHINE THEORY 2006年第10期41卷 1213-1229页

作者： Kalra, P. Mahapatra, P. B. Aggarwal, D. K. Punjab Engn Coll Dept Prod Engn Chandigarh India Punjab Engn Coll Dept Mech Engn Chandigarh India

The inverse kinematics solution of an industrial robot may provide multiple robot configurations that all achieve the required goal position of the manipulator. In the absence of obstacles, multiplicity resolution can be achieved by selecting the robot configuration closest to the current robot configuration in the joint space. An evolutionary approach based on a real-coded genetic algorithm is used to obtain the solution of the multimodal inverse kinematics problem of industrial robots. All the multiple configurations obtained by this approach can be displayed using a 3D modeler developed in MAT-LAB for the purpose of visualization. The multiple configurations are then compared on the basis of their closeness in joint space to the current robot configuration. Simulation experiments are carried out on a SCARA robot and a PUMA robot to illustrate the efficacy of the approach. (C) 2005 Elsevier Ltd. All rights reserved.

关键词： robot inverse kinematics real-coded genetic algorithm multiplicity resolution

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