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Designing and optimizing of composite and hybrid drive shafts based on the bees algorithm

JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY 2016年第4期30卷 1755-1761页

作者： Karimi, Saeed Salamat, Alireza Javadpour, Sirus Shiraz Univ Sch Engn Dept Mat Sci & Engn Shiraz Iran Shahid Chamran Univ Sch Engn Dept Mech Engn Ahvaz Iran

The main aim of this work is to introduce a novel approach to design and optimize of composite drive shafts based on bees algorithm (BA). BA was performed on a specific filament wound composite drive shaft which was supposed to be installed in a cooling tower. Three different composite laminates were optimized by BA to evaluate their final mass to cost ratio. The laminates were Glass fiber reinforced epoxy (GFRE), Carbon fiber reinforced epoxy (CFRE) and a hybrid of them. The conduction of BA led to just one optimum output for GFRE and CFRE;however, a cost-mass diagram including various acceptable solutions was the end result for the hybrid drive shaft. At the end, the BA predictions of the lowest cost optimized hybrid drive shaft were compared with the results of ANSYS simulations.

关键词： Drive shaft Filament winding bees algorithm Natural frequency Failure criteria

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Using the bees algorithm with Kalman filtering to train an artificial neural network for pattern classification

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING 2010年第I7期224卷 885-892页

作者： Pham, D. T. Darwish, A. Haj Cardiff Univ Mfg Engn Ctr Cardiff CF24 3AA S Glam Wales

The current paper presents the use of the bees algorithm with Kalman filtering to train a radial basis function (RBF) neural network. An enhanced fuzzy selection system has been developed to choose local search sites depending on the error and training accuracy of the RBF network. The paper provides comparative results obtained when applying RBF neural classifiers trained using the new bees algorithm, the original bees algorithm, and the conventional RBF procedure to an industrial pattern classification problem.

关键词： bees algorithm fuzzy logic Kalman filter neural network pattern classification

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The bees algorithm for workload balancing in examination job assignment

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EUROPEAN JOURNAL OF INDUSTRIAL ENGINEERING 2009年第4期3卷 424-435页

作者： Baykasoglu, Adil Ozbakir, Lale Tapkan, Pinar Gaziantep Univ Dept Ind Engn TR-27310 Gaziantep Turkey Erciyes Univ Dept Ind Engn TR-38039 Kayseri Turkey

In this paper, an integer quadratic programming model is proposed for workload balancing in the examination job assignment problem. The proposed model can be classified as part of the 'Generalised Assignment Problem' or GAP, which is known as an NP-hard problem. To solve the proposed model, a relatively new member of the swarm intelligence family known as the bees algorithm (BA) is used. The proposed mathematical model is also solved for nine sets of randomly generated test problems with a very well-known classical optimiser (CPLEX 10.1-MIQP) to present the competitive performance of the BA algorithm. The obtained results show that the proposed BA algorithm is able to generate better solutions with much shorter computational times.

关键词： assignment problems workload balancing metaheuristics swarm optimisation bees algorithm

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On the application of bees algorithm to the problem of crack detection of beam-type structures

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COMPUTERS & STRUCTURES 2011年第23-24期89卷 2169-2175页

作者： Moradi, S. Razi, P. Fatahi, L. Shahid Chamran Univ Dept Mech Engn Ahvaz 61355 Iran Dalhousie Univ Dept Civil & Resource Engn Halifax NS B3J 1Z1 Canada

In this paper, the application of the bees algorithm (BA) to the problem of crack detection in beams is introduced. A numerical as well as an experimental study is designed to predict a single open edge-crack in cantilever beams. The crack is modeled by a rotational spring, whose stiffness could be determined by the size of the crack. The weighted sum of the squared errors between the measured and computed natural frequencies is used as the objective function. The results show that both the size and location of the crack can be predicted well through this method. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： bees algorithm Crack detection Cantilever beam Particle swarm optimization Modal testing

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Combining the bees algorithm and shape grammar to generate branded product concepts

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE 2013年第12期227卷 1860-1873页

作者： Ang, M. C. Ng, K. W. Pham, D. T. Univ Kebangsaan Malaysia Inst Visual Informat Bangi 43600 Selangor Malaysia Univ Birmingham Sch Mech Engn Birmingham W Midlands England Ind Design Ctr Design Engn Sect Kuala Lumpur Malaysia

Generating product design concepts to meet functional requirements while maintaining a specific brand identity is a daunting task for a designer. Shape grammars have been applied to describe the creation of branded product shapes via a set of shape rules and were manually used to create a family of new design concepts, which maintain the product brand identity. Nevertheless, shape grammars are not able to evaluate whether the generated new product concepts can fulfil specified functional requirements of a product. In this research work, shape grammar is combined with an optimisation technique known as the bees algorithm to derive a computational architecture for generating branded design concepts that can meet a specified functional requirement. This combination approach allows shape rules to evolve while evaluating how well the outcomes of the new design concepts meet a specified functional requirement. This paper describes how the combination of the bees algorithm with shape grammar is created to generate branded product concepts, and shows that this approach can outperform a combination of shape grammar with an evolutionary algorithm.

关键词： bees algorithm branded product design evolutionary algorithms shape grammars

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The application of bees algorithm in finding the neutral stability curve for plane Poiseuille flow

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MECCANICA 2013年第9期48卷 2255-2261页

作者： Bahrainian, S. S. Mehrdoost, Z. Ghanbarzadeh, A. Shahid Chamran Univ Dept Mech Engn Ahvaz 61355 Iran

This paper investigates the application of the bees algorithm (BA) in finding the neutral stability curve of the Orr-Sommerfeld equation for basic flows between parallel plates. To demonstrate the performance of the proposed method, determination of neutral stability curve for plane Poiseuille flow is considered as a case study. Some minor modifications have been applied to BA in order to minimize the computational cost. To better assess the effectiveness of the bees algorithm, its results were compared with those of the modified genetic algorithm (MGA). The obtained results confirm the superiority of BA over MGA in terms of the computational cost.

关键词： bees algorithm Neutral stability curve Orr-Sommerfeld equation Plane Poiseuille flow

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A parallel bees algorithm implementation on GPU

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JOURNAL OF SYSTEMS ARCHITECTURE 2014年第3期60卷 271-279页

作者： Luo, Guo-Heng Huang, Sheng-Kai Chang, Yue-Shan Yuan, Shyan-Ming Natl Chiao Tung Univ Dept Comp Sci & Engn Hsinchu 300 Taiwan Natl Taipei Univ Dept Comp Sci & Informat Engn New Taipei City 237 Taiwan

bees algorithm is a population-based method that is a computational bound algorithm whose inspired by the natural behavior of honey bees to finds a near-optimal solution for the search problem. Recently, many parallel swarm based algorithms have been developed for running on GPU (Graphic Processing Unit). Since nowadays developing a parallel Bee algorithm running on the GPU becomes very important. In this paper, we extend the bees algorithm (CUBA (i.e. CUDA based bees algorithm)) in order to be run on the CUDA (Compute Unified Device Architecture). CUBA (CUDA based bees algorithm). We evaluate the performance of CUBA by conducting some experiments based on numerous famous optimization problems. Results show that CUBA significantly outperforms standard bees algorithm in numerous different optimization problems. (C) 2013 Elsevier B.V. All rights reserved.

关键词： bees algorithm Parallel bees algorithm Swarm intelligence GPGPU CUDA

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Bee for mining (B4M) - A novel rule discovery method using the bees algorithm with quality-weight and coverage-weight

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE 2019年第14期233卷 5101-5112页

作者： Packianather, Michael S. Al-Musawi, Ammar K. Anayi, Fatih Cardiff Univ Queens Buildings Cardiff CF24 3AA S Glam Wales Univ Wasit Minist Higher Educ & Sci Res Kut Iraq

This paper proposes a novel tool known as Bee for Mining (B4M) for classification tasks, which enables the bees algorithm (BA) to discover rules automatically. In the proposed B4M, two parameters namely quality-weight and coverage-weight have been added to the BA to avoid any ambiguous situations during the prediction phase. The contributions of the proposed B4M algorithm are two-fold: the first novel contribution is in the field of swarm intelligence, using a new version of BA for automatic rule discovery, and the second novel contribution is the formulation of a weight metric based on quailty and coverage of the rules discovered from the dataset to carry out Meta-Pruning and making it suitable for any classification problem in the real world. The proposed algorithm was implemented and tested using five different datasets from University of California, at Irvine (UCI Machine Learning Repository) and was compared with other well-known classification algorithms. The results obtained using the proposed B4M show that it was capable of achieving better classification accuracy and at the same time reduce the number of rules in four out of five UCI datasets. Furthermore, the results show that it was not only effective and more robust, but also more efficient, making it at least as good as other methods such as C5.0, C4.5, Jrip and other evolutionary algorithms, and in some cases even better.

关键词： Bee for mining (B4M) bees algorithm data mining classification rule discovery meta-pruning

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Automatic design of control systems for robot manipulators using the bees algorithm

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING 2012年第I4期226卷 497-508页

作者： Fahmy, A. A. Kalyoncu, M. Castellani, M. Cardiff Univ Inst Mech & Mfg Engn Cardiff Sch Engn Cardiff CF24 3AA S Glam Wales Selcuk Univ Fac Engn & Architecture Dept Mech Engn Konya Turkey Univ Bergen Dept Biol Bergen Norway

This paper proves the capability of the bees algorithm to solve complex parameter optimization problems for robot manipulator control. Two applications are presented. The first case considers the modelling of the inverse kinematics of an articulated robot arm using neural networks. The weights of the connections between the nodes need to be set so as to minimize the difference between the neural network model and the desired behaviour. In the proposed example, the bees algorithm is used to train three multilayer perceptrons to learn the inverse kinematics of the joints of a three-link manipulator. The second case considers the design of a hierarchical proportional-integral-derivative (PID) controller for a flexible single-link robot manipulator. The six gains of the PID controller need to be optimized so as to minimize positional inaccuracies and vibrations. Experimental tests demonstrated the validity of the proposed approach. In the first case, the bees algorithm proved very effective at optimizing the neural network models. Compared with the results obtained employing the standard back-propagation rule and an evolutionary algorithm, the bees algorithm obtained superior results in terms of training accuracy and robustness. In the second case, the proposed method demonstrated remarkable efficiency and consistency in the tuning of the PID controller parameters. In 50 independent optimization trials, the PID controllers designed using the bees algorithm consistently outperformed a robot controller designed using a standard manual technique.

关键词： bees algorithm robot control optimization inverse kinematics modelling neural networks hierarchical proportional-integral-derivative robot control

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bees algorithm for the Quadratic Assignment Problem on CUDA Platform 4th

Bees Algorithm for the Quadratic Assignment Problem on CUDA ...

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4th International Conference on Man-Machine Interactions (ICMMI)

作者： Chmiel, Wojciech Szwed, Piotr AGH Univ Sci & Technol PL-30059 Krakow Poland

ISBN: (纸本)9783319234373;9783319234366

With the proliferation of graphics processing units (GPU) supporting general-purpose computing (GPGPU), many computationally demanding applications are being redesigned to exploit the capabilities offered by massively parallel computing platforms. This paper presents a bees algorithm (BA) for the Quadratic Assignment Problem (QAP) implemented on the CUDA platform. The motivations for our work were twofold: firstly, we wanted to develop a dedicated algorithm to solve the QAP showing both time and optimization performance, secondly, we planned to check if the capabilities offered by popular GPUs can be exploited to accelerate hard optimization tasks requiring high computational power. The paper describes both sequential and parallel algorithm implementations, as well as reports results of tests.

关键词： QAP bees algorithm CUDA GPU calculation GPGPU Discrete optimization

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