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检索条件"主题词=artificial bee colony algorithm"

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An Effective Batching Method Based on the artificial bee colony algorithm for Order Picking

An Effective Batching Method Based on the Artificial Bee Col...

引用

9th International Conference on Natural Computation (ICNC)

作者： Li, Zhonghua Zhou, Zijing Sun Yat Sen Univ Sch Informat Sci & Technol Guangzhou 510275 Guangdong Peoples R China China Guangfa Bank Dept Informat Technol Guangzhou Guangdong Peoples R China

ISBN: (纸本)9781467347143

Order picking costs most of operating expenses in the warehouse management. Generally, order batching is effective in reducing the total travel distance of order picking. However, how to realize order batching is an NP-hard problem. It is difficult to find the optimal solution of order batching in polynomial time. Some deterministic methods are applied to small-scale order batching problems;while some heuristic algorithms are potential for large-scale order batching problems. Inspired by the behaviors of honey bee swarms, artificial bee colony (ABC) algorithms have been developed as potential computational approaches and performed well in scientific researches and engineering applications. To minimize the total travel distance of order picking, this paper proposes an effective batching method based on an artificial bee colony algorithm (ABC-BM). A series of numerical simulation experiments about order batching are arranged. Compared to GA-BM, the proposed ABC-BM algorithm is more efficient in optimizing different-scale order picking problems.

关键词： artificial bee colony algorithm order botching order picking warehouse management

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A Self Adaptive Hybrid artificial bee colony algorithm for Solving CEC 2013 Real-Parameter Optimization Problems

A Self Adaptive Hybrid Artificial Bee Colony Algorithm for S...

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IEEE/SICE International Symposium on System Integration (SII)

作者： Shan, Hai Yasuda, Toshiyuki Ohkura, Kazuhiro Hiroshima Univ Fac Engn Hiroshima Japan

ISBN: (纸本)9781479926268

artificial bee colony (ABC) algorithm is one of the most recently introduced swarm intelligence based algorithm which foraging the behavior of honey bee colonies. In order to improve the convergence performance and searching speed of finding best solution, self adaptive hybrid ABC (SAHABC) is proposed in this paper. For evaluating the performance of standard ABC and proposed SAHABC algorithms, we implemented experiments on CEC 2013 real-parameter single objective optimization problems testbed. SAHABC algorithm demonstrated competitive performance on the optimization problems with the dimension size of 10, 30, and 50 respectively.

关键词： activity based costing European Union institution Self bee colonies artificial bee colony algorithm Particle swarm optimization Parameter optimization Self tuning algorithms retrieval speed HYBRID Hybrid electric vehicles

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Automatic Image Enhancement by artificial bee colony algorithm

Automatic Image Enhancement by Artificial Bee Colony Algorit...

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4th International Conference on Graphic and Image Processing (ICGIP)

作者： Yimit, Adiljan Hagihara, Yoshihiro Miyoshi, Tasuku Hagihara, Yukari Iwate Univ Grad Sch Engn Morioka Iwate 020 Japan Iwate Univ Dept Mech Engn Morioka Iwate 020 Japan Iwate Univ Dept Elect Engn & Comp Sci Morioka Iwate 020 Japan

ISBN: (纸本)9780819495662

With regard to the improvement of image quality, image enhancement is an important process to assist human with better perception. This paper presents an automatic image enhancement method based on artificial bee colony (ABC) algorithm. In this method, ABC algorithm is applied to find the optimum parameters of a transformation function, which is used in the enhancement by utilizing the local and global information of the image. In order to solve the optimization problem by ABC algorithm, an objective criterion in terms of the entropy and edge information is introduced to measure the image quality to make the enhancement as an automatic process. Several images are utilized in experiments to make a comparison with other enhancement methods, which are genetic algorithm-based and particle swarm optimization algorithm-based image enhancement methods.

关键词： Image enhancement artificial intelligent optimization artificial bee colony algorithm

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Optimization of Facility Location Problem in Reverse Logistics Network using artificial bee colony algorithm

Optimization of Facility Location Problem in Reverse Logisti...

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IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

作者： Zhang, S. Z. Lee, C. K. M. Hong Kong Polytech Univ Dept Ind & Syst Engn Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781479909865

The management of used products attracts an increasing attention, which brings out the concept of Reverse Logistics. Reverse logistics is the reverse flow of surplus material back to the firm for reuse, repair, remanufacturing, recycling, and disposal of used products. In this research, we use the artificial bee colony (ABC) algorithm to solve the location and allocation problems of collection centers with the goal of minimizing total logistics costs. The performance of ABC algorithm is illustrated in our numerical experiments, which prove it is effective and efficient to handle the design of reverse logistics network. Our research provides useful insights of adopting of ABC algorithm for the optimization problems with multiple constrains.

关键词： Reverse logistics Collection center Facility location problem artificial bee colony algorithm

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A Discrete artificial bee colony algorithm for the Team Orienteering Problem with Time Windows

A Discrete Artificial Bee Colony Algorithm for the Team Orie...

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IEEE Symposium on Computational Intelligence in Production and Logistics Systems (CIPLS)

作者： Karabulut, Korhan Tasgetiren, M. Fatih Yasar Univ Software Engn Dept Selcuk Yasar Campus Izmir Turkey Yasar Univ Dept Ind Engn Izmir Turkey

ISBN: (纸本)9781467359054

This paper presents a discrete artificial bee colony algorithm (DABC) for solving the team orienteering problem with time windows (TOPTW). The proposed algorithm employs a destruction and construction procedure to generate neighboring food sources in the framework of the DABC algorithm. In addition, a variable neighborhood descent (VND) algorithm is developed to enhance the solution quality. The performance of the algorithm was tested on a benchmark set from the literature. Experimental results show that the proposed DABC algorithm is competitive to the best performing algorithms from the literature. Ultimately, 11 instances are further improved by the proposed DABC algorithm.

关键词： orienteering problem with time windows artificial bee colony algorithm iterated greedy algorithm swarm intelligence heuristic optimization

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A New Version of the Multiobjective artificial bee colony algorithm for Optimizing the Location Areas Planning in a Realistic Network

A New Version of the Multiobjective Artificial Bee Colony Al...

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2nd International Conference on the Theory and Practice of Natural Computing (TPNC)

作者： Berrocal-Plaza, Victor Vega-Rodriguez, Miguel A. Sanchez-Perez, Juan M. Univ Extremadura Escuela Politecn Dept Comp & Commun Technol Campus Univ S-N Caceres 10003 Spain

ISBN: (纸本)9783642450082;9783642450075

In this paper, we present our version of the MultiObjective artificial bee colony algorithm (a metaheuristic based on the foraging behavior of honey bees) to optimize the Location Areas Planning Problem. This bi-objective problem models one of the most important tasks in any Public Land Mobile Network: the mobile location management. In previous works of other authors, this management problem was simplified by using the linear aggregation of the objective functions. However, this technique has several drawbacks. That is the reason why we propose the use of multiobjective optimization. Furthermore, with the aim of studying a realistic mobile environment, we apply our algorithm to the mobile network developed by the Stanford University (a mobile network located in the San Francisco Bay, USA). Experimental results show that our proposal outperforms other algorithms published in the literature.

关键词： Location Areas Planning Problem Mobile Location Management Multiobjective Optimization Stanford University Mobile Activity Traces artificial bee colony algorithm

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Optimization of LQR Controller for Inverted Pendulum System with artificial bee colony algorithm

Optimization of LQR Controller for Inverted Pendulum System ...

引用

International Conference on Advanced Mechatronic Systems (ICAMechS)

作者： Wang, Haiquan Zhou, Huaqiang Wang, Dongyun Wen, Shengjun Zhongyuan Univ Technol Dept Elect & Informat Zhengzhou Peoples R China

ISBN: (纸本)9781479925186;9781479925193

As a strong coupled nonlinear under-actuated system, the balance control of the circular-rail double inverted pendulum system is discussed in this paper. Firstly, the linear quadratic regulator is established based on the mathematical model of the plant which is linearized about the pendulum's upright equilibrium position. In order to obtain the optimal control performance, as well as to avoid repeated adjustment of LQR parameters, artificial bee colony(ABC) algorithm as a new meta-heuristic approach inspired by intelligent foraging behavior of honeybee swarm is introduced for the parameters optimization of Q and R during LQR controller design. The simulation with the circular-rail double inverted pendulum is conducted to demonstrate the effectiveness of the LQR control strategy as well as the ABC optimization algorithm.

关键词： inverted pendulum LQR artificial bee colony algorithm

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A Novel Modulation Recognition Technique Based on artificial bee colony algorithm in the Presence of Multipath Fading Channels

A Novel Modulation Recognition Technique Based on Artificial...

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36th International Conference on Telecommunications and Signal Processing (TSP)

作者： Ozen, Ali Ozturk, Celal Nuh Naci Yazgan Univ TR-38010 Kayseri Turkey Erciyes Univ TR-38039 Kayseri Turkey

ISBN: (纸本)9781479904020;9781479904037

In this paper, a novel automatic modulation recognition (AMR) method has been proposed for classifying of the transmitted signals by observing the received data samples in the presence of additive white Gaussian noise (AWGN) and multipath fading channel. The proposed method (ABC-ANN) is based on artificial neural network (ANN) which is trained by artificial bee colony (ABC) algorithm. Because high order statistics are very interesting features to solve the problem of AMR, the high order cumulants have been employed in the proposed ABC-ANN classifier. ABC algorithm is used in finding the optimal weight set of artificial neural networks for classification and the performance of the proposed ABC-ANN algorithm is compared with the performance of ANN classifier (SCG-ANN) using scaled conjugate gradient learning algorithm. Computer simulation results have demonstrated that the proposed recognizer can reach much better classification accuracy than the SCG-ANN in even 0 dB of signal to noise ratio (SNR) value.

关键词： Automatic modulation recognition artificial bee colony algorithm artificial neural networks high order cumulant

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Multi-level threshold Image Segmentation using artificial bee colony algorithm

Multi-level threshold Image Segmentation using Artificial Be...

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5th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA)

作者： Hu Zhihui Yu Weiyu Lv Shanxiang Feng Jiuchao S China Univ Technol Sch Elect & Informat Engn Guangzhou 510640 Guangdong Peoples R China

ISBN: (纸本)9780769549323;9781467356527

Image segmentation is still a crucial problem in image processing. In this paper, we proposed a novel multi-level image segmentation method based on PSNR using artificial bee colony algorithm (ABCA). PSNR is considered as an objective function of ABCA. The best multi-level thresholds (t(1)*, t(2)*, ... , t(n-1)*, t(n)*) are those which can make the PSNR maximize. Further, we compare entropy and PSNR in segmenting gray-level images and noisy images. Through experiments, it is found that the entropy isn't suitable to be applied to segmentation of images with Gaussian noise. So we can conclude that entropy can't be used for noisy image segmentation. The experiments results demonstrate our proposed method is effective and efficient.

关键词： artificial bee colony algorithm Image segmentation Multi-level threshold PSNR

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The Development of an Automatic Question Generation System on Facebook Using an artificial bee colony algorithm

The Development of an Automatic Question Generation System o...

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International Conference on Information, Communication and Engineering (ICICE 2012)

作者： Chen, Hsin-Chin Hsu, Chia-Cheng Li, Hung-Chang Huang, Chih-Chin Huang, Yueh-Min Natl Cheng Kung Univ Dept Engn Sci Tainan 701 Taiwan

ISBN: (纸本)9783037856727

Facebook is currently one of the world's most popular social networking services, and has been widely used in the field of e-learning. In general, learners in e-learning environments need to evaluate their learning ability through taking tests to present the learning achievement. In order to evaluate their ability on e-learning platform with social network services, this study proposes an automatic question generation system for individual learning status. The proposed system uses the artificial bee colony algorithm to find suitable questions for each learner according to the learner's profile, reading experience, professional ability, and the e-learning records in the system. The experimental results indicate that the proposed method improves the accuracy of the automatic question generation system and that it outperforms the random method.

关键词： Social Networking Service E-Learning Computerized Adaptive Testing artificial bee colony algorithm

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