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Novel genetic algorithm for short-term scheduling of sequence dependent changeovers in multiproduct polymer plants

COMPUTERS & CHEMICAL ENGINEERING 2011年第12期35卷 2945-2959页

作者： Ramteke, Manojkumar Srinivasan, Rajagopalan Natl Univ Singapore Dept Chem & Biomol Engn Singapore 117576 Singapore ASTAR Inst Chem & Engn Sci Jurong Isl 627833 Singapore

Polymer plants generally operate to produce different grades of product from the same reactor. Such systems commonly require short-term scheduling to meet market demand. One important requirement in continuous-time scheduling of such systems is to satisfy a variety of constraints, including identifying feasible sequences of the predecessor and successor jobs to effectively handle changeovers. In this study, a new genetic algorithm (GA) is proposed to solve such job sequencing problems. The proposed GA uses real-coded chromosome to represent job orders and their sequences in the schedule. The novelty is that the representation ensures that all constraints are satisfied a priori, except the sequence constraint which is handled by penalizing violations. Three important problems relevant to polymer industry are solved to obtain optimal schedules. The first deals with the sequencing constraint between individual product orders, the second with sequencing constraint between groups of product orders, while the third incorporates batching with scheduling. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Grades Multi-objective optimization real-coded genetic algorithm Linear programming Stochastic modeling

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Optimization of natural frequencies of bidirectional functionally graded beams

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STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION 2006年第6期32卷 473-484页

作者： Goupee, Andrew J. Vel, Senthil S. Univ Maine Dept Mech Engn Orono ME 04469 USA

We propose a methodology to optimize the natural frequencies of functionally graded structures by tailoring their material distribution. The element-free Galerkin method is used to analyze the two-dimensional steady-state free and forced vibration of functionally graded beams. To optimize the material composition, the spatial distribution of volume fractions of the material constituents is defined using piecewise bicubic interpolation of volume fraction values that are specified at a finite number of grid points. Subsequently, we use a real-coded genetic algorithm to optimize the volume fraction distribution for three model problems. In the first problem, we seek material distributions that maximize each of the first three natural frequencies of a functionally graded beam. The goal of the second model problem is to minimize the mass of a functionally graded beam while constraining its natural frequencies to lie outside certain prescribed frequency bands. The last problem aims to minimize the mass of a functionally graded beam by simultaneously optimizing its thickness and material distribution such that the fundamental frequency is greater than a prescribed value.

关键词： heterogeneous solid FGM inhomogeneous material element-free Galerkin method real-coded genetic algorithm

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The performance verification of an evolutionary canonical particle swarm optimizer

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NEURAL NETWORKS 2010年第4期23卷 510-516页

作者： Zhang, Hong Ishikawa, Masumi Kyushu Inst Technol Dept Brain Sci & Engn Grad Sch Life Sci & Syst Engn Kitakyushu Fukuoka 8080196 Japan

We previously proposed to introduce evolutionary computation into particle swarm optimization (PSO), named evolutionary PSO (EPSO). It is well known that a constricted version of PSO, i.e., a canonical particle swarm optimizer (CPSO), has good convergence property compared with PSO. For further improving the search performance of an CPSO, we propose in this paper a new method called an evolutionary canonical particle swarm optimizer (ECPSO) using the meta-optimization proposed in EPSO. The ECPSO is expected to be an optimized CPSO in that optimized values of parameters are used in the CPSO. We also introduce a temporally cumulative fitness function into the ECPSO to reduce stochastic fluctuation in evaluating the fitness function. Our experimental results indicate that (1) the optimized values of parameters are quite different from those in the conventional CPSO: (2) the search performance by the ECPSO, i.e., the optimized CPSO, is superior to that by CPSO, OPSO, EPSO, and RGA/E except for the Rastrigin problem. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： Evolutionary particle swarm optimization Canonical particle swarm optimizer Temporally cumulative fitness function real-coded genetic algorithm Exploitation and exploration Model selection

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Mathematical modelling and two-stage identification for a motor-toggle mechanism with clamping effect

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APPLIED MATHEMATICAL MODELLING 2016年第19-20期40卷 8660-8670页

作者： Hsu, Yi-Lung Fung, Rong-Fong Natl Kaohsiung First Univ Sci & Technol Dept Mech & Automat Engn 1 Univ Rd Kaohsiung 824 Taiwan

The effect of clamping forces on a motor-toggle mechanism is dynamically modeled in this paper, and the clamping unit is presented by a simple spring-damper model. Based on real practical applications, the impact force model (IFM) associated with clamping effectiveness must be considered during the process of clamping. A two-stage identification method is also needed to develop for validating dynamic responses of the unclamping and clamping motions. The real-coded genetic algorithm (RGA) is employed to obtain system's parameters by two different fitness functions. The RGA feasibility is verified by the assigned parameters in numerical simulations, and then applied to the experimental physical model. Finally, numerical simulations and experimental results showed good agreement, and the proposed two-stage identification method described in this paper is found to be both better and necessary for the mechatronic system with a clamping unit. (C) 2016 Elsevier Inc. All rights reserved.

关键词： Clamping unit Impact force model real-coded genetic algorithm Two-stage identification

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Engine test data modelling by evolutionary radial basis function networks

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2003年第D6期217卷 489-497页

作者： Lin, W Wu, MH Duan, S Univ Derby Sch Engn Derby DE22 1GB England Gaydon Test Ctr Warwick England

The engine test bed is introduced briefly and the importance of modelling for the engine test is discussed. The application of combining radial basis function (RBF) networks and a real-coded genetic algorithm (RCGA) to create the model is described for the engine test. Finally, the experimental results are analysed and it is shown that the proposed approach combining RCGA and RBF models is well suited for the engine test data modelling task.

关键词： radial basis function network genetic algorithm real-coded genetic algorithm modelling neural network

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Generate optimal grasping trajectories to the end-effector using an improved genetic algorithm

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ADVANCES IN SPACE RESEARCH 2020年第7期66卷 1803-1817页

作者： Wang, Mingming Luo, Jianjun Zheng, Lili Yuan, Jianping Walter, Ulrich Northwestern Polytech Univ Shenzhen Inst Res & Dev Shenzhen 518057 Peoples R China Northwestern Polytech Univ Sch Astronaut Natl Key Lab Aerosp Flight Dynam Xian 710072 Peoples R China Beijing Inst Aerosp Syst Engn Beijing 100076 Peoples R China Tech Univ Munich Inst Astronaut D-85748 Garching Germany

Determining how to grasp a non-cooperative target by applying a space robot is still a challenging issue, especially when the target is tumbling in space. This paper presents an optimal grasp planning strategy for a kinematically redundant space manipulator to capture an arbitrarily rotating target, such as a dysfunctional satellite or a piece of space debris. The kinematics and dynamics of the non-cooperative target and the space robotic system are first introduced, which lays the foundation for constructing the grasp planning strategy. Subsequently, an optimal grasping time and the target's terminal motion states are determined with consideration of the robotic capability, the target's motion and the grasping direction. Furthermore, the joint trajectories are parametrized with the quintic Bezier curve, and the direct kinematics equations are employed to overcome the dynamics singularity issue. The grasp planner of the space robot is then transformed into a multi-constraint, multi-objective nonlinear optimization problem solved by an improved real-coded genetic algorithm (RGA). The proposed grasp planning scheme is immune to the singularity issue and generates an optimal robotic configuration for post-capture manipulation. Simulation results are presented for capturing a tumbling target using a seven-degree-of-freedom kinematically redundant manipulator mounted on a free-floating spacecraft, demonstrating the effectiveness of the proposed method. (c) 2020 COSPAR. Published by Elsevier Ltd. All rights reserved.

关键词： Grasp planning Free-floating Bezier curve real-coded genetic algorithm

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System identification of a dual-stage XY precision positioning table

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PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY 2009年第1期33卷 71-80页

作者： Fung, Rong-Fong Hsu, Yi-Lung Huang, Ming-Shyan Natl Kaohsiung First Univ Sci & Technol Grad Inst Electroopt Engn Kaohsiung 824 Taiwan Natl Kaohsiung First Univ Sci & Technol Dept Mech & Automat Engn Kaohsiung 824 Taiwan

The purpose of this study is to develop a micro/nano-meter XY precision positioning table, in which the coarse and fine positionings are performed by the permanent magnet synchronous motor (PMSM) and piezoelectric actuator (PA), respectively. The main contribution is to identify the XY table driven by the PM and PA, where the Bouc-Wen hysteresis phenomenon of the PA and cross-coupling effects between the X and Y axes are included. In system identification, the real-coded genetic algorithm (RGA) method is employed to find the optimized parameters, where the parameter identification is divided into the individual and integral identifications, and their numerical simulations and experimental results are compared. In conclusion, the dual-stage XY precision positioning table driven by the PM and the PA including the cross-coupling and hysteresis phenomenon can be successfully identified, and it is found that the identified parameters by the integral identification are better. (c) 2008 Elsevier Inc. All rights reserved.

关键词： Bouc-Wen hysteresis model Cross-coupling effect real-coded genetic algorithm System identification

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Signal quality improvement of holographic data storage using adaptive two-dimensional filter

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OPTICAL REVIEW 2010年第3期17卷 204-209页

作者： Takahata, Yosuke Kondo, Yo Yoshida, Shuhei Yamamoto, Manabu Tokyo Univ Sci Fac Ind Sci & Technol Chiba 2788510 Japan

Holographic data storage is being widely studied for the purpose of developing next-generation large optical memories. A prospective use of this type of memory is in building image archives in large-scale data centers. In particular, demand for energy conservation at data centers, and therefore for holographic data storage, is growing. In holographic data storage, interference between bits occurs owing to wave aberration in the optical system, shrinkage of the medium, and crosstalk noise from neighboring holograms during multiplex recording;as a result of the interference, the reproduced image deteriorates and the bit error rate (BER) increases. In this study, to reduce the BER in both off-axis-type recording and coaxial-type recording, a two-dimensional finite impulse response (FIR) filter is applied to a reproduced image that has been recorded by angle multiplex recording and shift multiplex recording. First, for the optimization of the FIR filter coefficients, the linear minimum mean square error (LMMSE) method is applied;this method optimizes the coefficients by reducing the BER. Furthermore, for evaluating the optimization performance of the LMMSE method, the optimization performance is compared with that of the real-coded genetic algorithm (RCGA), which has the capability to search a wide range of coefficients. The optimization by the LMMSE method has been found to be excellent for off-axis-type recording but not for coaxial-type recording. It is speculated that this is because of the brightness irregularity in the reproduced image, resulting from crosstalk. On the other hand, a marked reduction in the BER is observed using the RCGA, despite the brightness irregularity. In this study, the effectiveness of the LMMSE method for signals recorded by coaxial-type recording, in which large brightness irregularity is expected, is examined using automatic gain control (AGC). It is found that the application of AGC reduces the BER even in the case of coaxial-type recor

关键词： holographic data storage bit error rate optimization FIR filter real-coded genetic algorithm linear minimum mean squared error automatic gain control

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REDUCING INFLUENCE OF ECCENTRIC LOAD ON DYNAMIC CHARACTERISTICS OF ROTARY ACTUATOR

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INTERNATIONAL JOURNAL OF FLUID POWER 2007年第2期8卷 17-24页

作者： Qian, Ye GuoXiang, Meng Shanghai Jiao Tong Univ Sch Mech Engn SMC Pneumat Tech Ctr Dong Chuan Rd 800 Shanghai 200240 Peoples R China

The main objective of this study is to reduce the eccentric load's influence on the dynamic characteristics of a horizontally installed rotary actuator. The solution is drilling a hole into the rotary shaft of a rotary cylinder. With the rotation of the rotary actuator the hole will open and connect the two working chambers within a certain angular range, the back pressure will increase and the torque introduced by the back pressure partly compensates for the torque of the eccentric load. The design procedure for the connecting hole is as follows: First, experiments that study the effect of eccentric loads on the dynamic characteristics of a rotary actuator were carried out, and a stability index a(v) was proposed;Second, a mathematical model including the connecting hole was built;Third, a real-coded GA optimization design for the connecting hole whose object is to minimize av was conducted. Simulations and test results show that the method worked efficiently.

关键词： pneumatic rotary actuator eccentric load instability real-coded genetic algorithm optimization design

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Application of genetic algorithm-based intuitionistic fuzzy weighted c-ordered-means algorithm to cluster analysis

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KNOWLEDGE AND INFORMATION SYSTEMS 2021年第7期63卷 1935-1959页

作者： Kuo, R. J. Chang, C. K. Nguyen, Thi Phuong Quyen Liao, T. W. Natl Taiwan Univ Sci & Technol Dept Ind Management 43Sect 4Kee Lung Rd Taipei 106 Taiwan Micron Memory Taiwan Co Ltd 369Sec 4Sanfeng Rd Taichung 42152 Taiwan Univ Sci & Technol Univ Danang Fac Project Management 54 Nguyen Luong Bang Danang Vietnam Louisiana State Univ Dept Mech & Ind Engn Baton Rouge LA 70808 USA

With the advance of information technology, many fields have begun using data clustering to reveal data structures and obtain useful information. Most of the existing clustering algorithms are susceptible to outliers and noises as well as the initial solution. The fuzzy c-ordered-means (FCOM) method can handle outlier and noise problems by using Huber's M-estimators and Yager's OWA operator to enhance its robustness. However, the result of the FCOM algorithm is still unstable because its initial centroids are randomly generated. Besides, the attributes' weight also affect the clustering performance. Thus, this study first proposed an intuitionistic fuzzy weighted c-ordered-means (IFWCOM) algorithm that combines intuitionistic fuzzy sets (IFSs), the feature-weighted and FCOM together to improve the clustering result. Moreover, this study proposed a real-coded genetic algorithm-based IFWCOM (GA-IFWCOM) that employs the genetic algorithm to exploit the global optimal solution of the IFWCOM algorithm. Twelve benchmark datasets were used for verification in the experiment. According to the experimental results, the GA-IFWCOM algorithm achieved better clustering accuracy than the other clustering algorithms for most of the datasets.

关键词： Clustering analysis Fuzzy c-ordered-means algorithm Feature-weighted Intuitionistic fuzzy sets Outlier real-coded genetic algorithm

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