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

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artificial bee colony algorithm with Dynamic Dimension Search

Artificial bee Colony Algorithm with Dynamic Dimension Searc...

引用

Cloud Computing, Big Data Applications and Software Engineering (CBASE), International Conference on

作者： Ming Zhao Meiyu Wang School of Computer Science and Engineering Shenyang Jianzhu University Liaoning China

ISBN: (数字)9798331506582

ISBN: (纸本)9798331506599

Aiming at the shortcomings of the standard artificial bee colony (ABC) algorithm due to weak exploitation capability and slow convergence speed caused by one-dimension search, an ABC algorithm with dynamic dimension search (DDSABC) is proposed. Firstly, a dynamic selection mechanism for dimension search strategy is designed, where one-dimension search is used in the early stage of search to exploit globally diverse individuals, and multi-dimension search is used in the late stage to explore convergent individuals; an elite moderately guided dimension selection mechanism is designed for multi-dimension search, where half of the dimensions are selected under the guidance of the elite mean to accelerate the evolution of potential dimensions, and the other half are selected by a randomized way to maintain a moderate randomness; in addition, suitable search equations are selected for the different characteristics of the two dimension search strategies to ensure the balance between exploration and exploitation capabilities. Finally, on 30 complex problems from the CEC2014 test set, ablation experiments and comparative experiments with the standard ABC and its 5 variants are analyzed, and the results show that the proposed algorithm in this paper performs better in terms of solution accuracy, stability and convergence speed.

关键词： Cloud computing Accuracy Heuristic algorithms Software algorithms Search problems artificial bee colony algorithm Stability analysis Standards Convergence Software engineering

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artificial bee colony algorithm for Optimization in Energy-saving Elevator Group Control System

Artificial Bee Colony Algorithm for Optimization in Energy-s...

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International Conference on Electrical & Electronic Engineering (ICEEE)

作者： Mohammad Hanif Nur Mohammad Kazi Tanvir Ahmmed Chittagong University of Engineering & Technology Chittagong Bangladesh University of Chittagong Chittagong Bangladesh

ISBN: (纸本)9781665482820

Due to the involvement of multiple unpredictable factors, optimization in Elevator Group Control System (EGCS) is a challenging task. The major optimization parameters in most previous research articles were the passengers’ average waiting time (AWT) or average journey time (AJT). Owing to the global energy crisis, however, optimizing the energy-consumption in EGCS has become a pivotal issue. In order to overcome this concern, an optimization approach utilizing artificial bee colony (ABC) algorithm, which has never been applied in EGCS, is implemented in this study. Furthermore, the performance of this ABC algorithm in energy-saving EGCS is compared to that of Genetic algorithm (GA), another popular swarm intelligence algorithm. According to the comparisons, ABC is better at minimizing energy-consumption by avoiding trapping in local minima when compared to GA. Most notably, in 100 independent simulations, this ABC algorithm exhibits substantially lower standard deviation than that of GA.

关键词： Computational modeling artificial bee colony algorithm Control systems Elevators Task analysis Particle swarm optimization Optimization

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Makespan Minimization in Aircraft Landing Problem Under Congested Traffic Situation Using Modified artificial bee colony algorithm

Makespan Minimization in Aircraft Landing Problem Under Cong...

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

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

ISBN: (纸本)9781509036653

Due to the increase in air transportation demand, runway capacity is reaching a bottleneck at the international airports, especially during peak hours. Managing on aircraft sequencing or sequencing problems in airport perspective have become a crucial operation nowadays in order to maintain safety landing and utilize the runway facility to handle the schedules for all incoming aircraft under congestion. The traditional approach allows aircraft to remain an economic speed during approaching to the airport. However, such approach may not be applicable in congested air traffic situation. Therefore, the makespan minimization is more practical for the rescheduling efforts afterwards. This article presents a modified artificial bee colony algorithm to obtain nearly optimal solution to support the air tower controller in order to obtain last-minute decisions of landing sequence. The modified artificial bee colony algorithm for aircraft landing problem provides a promising optimal search within 6.1 seconds to handle last-minute disruption.

关键词： Aircraft landing problem Air traffic control Meta-heuristics artificial bee colony algorithm

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An Elite Group Guided artificial bee colony algorithm with a Modified Neighborhood Search 15th

An Elite Group Guided Artificial Bee Colony Algorithm with a...

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15th Pacific Rim International Conference on artificial Intelligence (PRICAI) / 15th Pacific Rim Knowledge Acquisition Workshop (PKAW)

作者： Lu, Jiaxin Zhou, Xinyu Ma, Yong Wang, Mingwen Jiangxi Normal Univ Sch Comp & Informat Engn Nanchang 330022 Jiangxi Peoples R China

ISBN: (纸本)9783319973104;9783319973098

artificial bee colony (ABC) algorithm is a powerful global optimization method. For some complex optimization problems, however, ABC also suffers from a slow convergence speed due to its solution search equation which has strong exploration ability but poor exploitation ability. To solve the defect, in this paper, we proposed an elite group guided ABC algorithm with a modified neighborhood search operator, which aims to utilize the valuable information of elite individuals to guide search. First, some food sources with good fitness values are chosen as the elite individuals, and then they are used to construct an elite group. Second, in the onlooker bee phase, a novel solution search equation is designed based on the elite group, which introduces a parameter MR (modification rate) to control the greediness degree of the elite group guidance. Last, a modified neighborhood search operator is proposed based on the elite group, which is exploited to produce fine search in the vicinity of the elite individuals for a better tradeoff between exploration and exploitation abilities. In the experiments, 22 well-known test functions were used. The experimental results compared with other five ABC variants showed that our approach can achieve better or at least comparable performance on most of the test functions.

关键词： artificial bee colony algorithm Solution search equation Elite group Neighborhood search

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Classifying Piper Nigrum using artificial bee colony algorithm 4

Classifying Piper Nigrum using Artificial Bee Colony Algorit...

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4th IEEE International Conference on artificial Intelligence with applications in Engineering and Technology (ICAIET)

作者： Yusup, Norfadzlan Iskandar, D. N. F. Awang Hassan, Siti Hazemah Univ Malaysia Sarawak Fac Comp Sci & Informat Technol Kota Samarahan 94300 Sarawak Malaysia

ISBN: (纸本)9781479979103

Pepper grading is one of the key elements in assuring the quality of the traded pepper. Currently, the pepper grading process performed by Malaysia Pepper Board (MPB) is semi-automated where a commercial colour sorter is used to distinguish white premium pepper and this grading process is very time consuming. In this paper we present the framework for pepper grading using the artificial bee colony algorithm (ABC) to classify the white pepper berries from digital images. Our initial experiment on the image features indicates that colour, shape and textures could be used as the parameters for the ABC algorithm for classifying the pepper berries into its respective grades.

关键词： artificial bee colony algorithm image processing and classification agricultural science

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Fuzzy optimal power flow with multi-objective based on artificial bee colony algorithm in power system

Fuzzy optimal power flow with multi-objective based on artif...

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International Conference on Renewable Energy and Environmental Technology (REET 2013)

作者： He, Xuanhu Wang, Wei Wang, Yingnan Kong, Jun Geng, Jing Fan, Shengbin Beijing JiaoTong Univ Sch Elect Engn Beijing Peoples R China

ISBN: (纸本)9783037859124

According to the problem of optimal power flow (OPF), the optimization objectives including minimization of total fuel cost for generating units, minimization of emission for atmospheric pollutants, minimization of active power losses and minimization of voltages deviations are established. The paper uses fuzzy membership functions instead of multi-objective functions to form fuzzy optimal power flow in the optimal power flow calculation process. The novel artificial bee colony (ABC) algorithm is proposed to solve OPF problem with multi-objective. The proposed approach is applied to the OPF problem on IEEE30 test systems. And the simulation results verify the effectiveness of the proposed method.

关键词： Power System Optimal Power Flow Fuzzy Mathematics Multi-objective Function artificial bee colony algorithm

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THE artificial bee colony algorithm FOR VECTOR QUANTIZATION IN IMAGE COMPRESSION

THE ARTIFICIAL BEE COLONY ALGORITHM FOR VECTOR QUANTIZATION ...

引用

4th IEEE International Conference on Broadband Network and Multimedia Technology (IEEE IC-BNMT 2011)

作者： Horng, Ming-Huwi Jiang, Ting-Wei Natl PingTung Inst Commerce Dept Comp Sci & Informat Engn Pingtung Taiwan

ISBN: (纸本)9781612841564

The vector quantization was a powerful technique in image compression. The widely used method _ such as the Linde-Buzo-Gray (LBG) algorithm always generated local optimal codebook. Recently, particle swarm optimization was adapted to obtain the near-global optimal codebook of vector quantization. The alterative method called the quantum particle swami optimization was developed to improve the results of original PSO algorithm. The honey bee mating optimization was used to develop the algorithm for vector: quantization. In this paper, we proposed a new method based on the artificial bee colony (ABC) algorithm to construct the codebook of vector quantization. The proposed method use LBG method as the initial of ABC algorithm to develop the VQ algorithm. This method is called ABCLBG algorithm. The ABC-LBG algorithm is compared with four algorithms described above. Experimental results showed that the ABC-LBG algorithm-is more-reliable and the reconstructed images get higher quality compared to other methods.

关键词： Vector quantization LBG algorithm Particle swarm optimization Quantum particle swarm optimization Honey bee mating optimization 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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An Adaptive Unified artificial bee colony algorithm for Global Optimization 30

An Adaptive Unified Artificial Bee Colony Algorithm for Glob...

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30th Chinese Control and Decision Conference (CCDC)

作者： Yang, Yang Xu, Feiyi Hu, Haidong Gao, Hao Nanjing Univ Posts & Telecommun Inst Adv Technol Nanjing Peoples R China Beijing Inst Control Engn Beijing Peoples R China

ISBN: (纸本)9781538612446

The artificial bee colony (ABC) algorithm invented by Karaboga is a relative new nature inspired heuristic for optimization problem. It has been proved to be competitive with some conventional optimization algorithms. This paper proposes an adaptive unified artificial bee colony (auABC) algorithm which employs a single equation unifying multiple strategies into one expression. As we all know, ABC is good at exploration but poor at exploitation due to the insufficiency in its solution search equation and its one-dimensional search strategy leads to slower convergence speed. In order to improve the above defects, we created a combined self-adaptive equation that its parameters are determined by the current iteration times to solve the problem mentioned above. We also introduce a chaotic strategy when generating candidate food sources which balance the proportion of exploration and exploitation. Experiments conducted on benchmark functions demonstrate that our algorithm achieves good performance in both unimodal and multimodal functions as expected compared to several state-of-the-art algorithms.

关键词： artificial bee colony algorithm Solution search equation Adaptive strategy

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Multi-objective artificial bee colony algorithm 7

Multi-objective Artificial Bee Colony algorithm

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7th International Conference on Computational Intelligence and Communication Networks (CICN)

作者： Wang, Yanjiao Li, Yaojie Northeast Dianli Univ Sch Informat Engn Jilin Shi Jilin Peoples R China

ISBN: (纸本)9781509000760

In order to approach the true Pareto front as fast as possible and make the distribution of solutions uniform on multi-objective optimization problems, a multi-objective optimization algorithm based on artificial bee colony algorithm has been presented in this paper, named MABC. Firstly, a novel selection scheme, which is used to guide the population evolution towards the true Pareto front and keep population diversified, substitutes the roulette wheel selection scheme. Secondly, the adaptive searching models are designed for the employed bees and onlookers, in which the convergence rate and diversity are considered simultaneously. Finally, an improved method of determining elite population is proposed to maintain diversity. Compared with other state-of-the-art algorithms, the simulation results of 5 standard test functions show that MABC achieves comparable results in terms of diversity and convergence metrics.

关键词： multi-objective optimization artificial bee colony algorithm adaptive searching scheme diversity maintenance

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