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Coupling Optimization Design of Aspirated Compressor Airfoil and Aspirated Scheme Based on artificial bee colony algorithm and CST Method

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INTERNATIONAL JOURNAL OF TURBO & JET-ENGINES 2015年第1期32卷 25-39页

作者： Li, Jun Liu, Bo Zhao, Yan Yang, Xiaodong Lu, Xiaofeng Wang, Lei Northwestern Polytech Univ Sch Power & Energy Xian 710072 Shaanxi Peoples R China AVIC Shenyang Engine Design & Res Inst Shenyang Liaoning Peoples R China AVIC Aerodynam Res Inst Shenyang Liaoning Peoples R China

This paper focuses on creating a new design method optimizing both aspirated compressor airfoil and the aspiration scheme simultaneously. The optimization design method is based on the artificial bee colony algorithm and the CST method, while the flow field is computed by one 2D computational program. The optimization process of the rotor tip and stator tip airfoil from an aspirated fan stage is demonstrated to verify the effectiveness of the new coupling method. The results show that the total pressure losses of the optimized stator tip and rotor tip airfoil are reduced relatively by 54% and 20%, respectively. artificial bee colony algorithm and CST method indicate a satisfying applicability in aspirated airfoil optimization design. Finally, the features of aspirated airfoil designing process are concluded.

关键词： aspirated compressor airfoil aspirated scheme coupling optimization design artificial bee colony algorithm CST method

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Crossover-based artificial bee colony algorithm for constrained optimization problems

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NEURAL COMPUTING & APPLICATIONS 2015年第7期26卷 1587-1601页

作者： Brajevic, Ivona Univ Belgrade Fac Math Belgrade 11000 Serbia

artificial bee colony (ABC) algorithm represents one of the most-studied swarm intelligence algorithms. Since the original ABC has been found to be very effective, today there are a lot of improved variants of ABC algorithm used to solve a wide range of hard optimization problems. This paper describes a novel artificial bee colony algorithm for constrained optimization problems. In the proposed algorithm, five modifications are introduced. Firstly, to improve the exploitation abilities of ABC, two different modified ABC search operators are used in employed and onlooker phases, and crossover operator is used in scout phase instead of random search. Secondly, modifications related to dynamic tolerance for handling equality constraints and improved boundary constraint-handling method are employed. The experimental results, obtained by testing on a set of 24 well-known benchmark functions and four widely used engineering design problems, show that the proposed approach can outperform ABC-based approaches for constrained optimization problems in terms of the quality of the results, robustness and convergence speed. Additionally, it provides better results in most cases compared with other state-of-the-art algorithms.

关键词： artificial bee colony algorithm Constrained optimization Nature-inspired algorithms Swarm intelligence Exploitation Exploration

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A new modified artificial bee colony algorithm for the economic dispatch problem

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ENERGY CONVERSION AND MANAGEMENT 2015年第Jan.期89卷 43-62页

作者： Secui, Dinu Calin Univ Oradea Dept Energy Engn Oradea 410087 Romania

In this paper a new modified artificial bee colony algorithm (MABC) is proposed to solve the economic dispatch problem by taking into account the valve-point effects, the emission pollutions and various operating constraints of the generating units. The MABC algorithm introduces a new relation to update the solutions within the search space, in order to increase the algorithm ability to avoid premature convergence and to find stable and high quality solutions. Moreover, to strengthen the MABC algorithm performance, it is endowed with a chaotic sequence generated by both a cat map and a logistic map. The MABC algorithm behavior is investigated for several combinations resulting from three generating modalities of the chaotic sequences and two selection schemes of the solutions. The performance of the MABC variants is tested on four systems having six units, thirteen units, forty units and fifty-two thermal generating units. The comparison of the results shows that the MABC variants have a better performance than the classical ABC algorithm and other optimization techniques. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Economic/emission dispatch artificial bee colony algorithm Chaotic maps Valve-point effects Transmission losses

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A Membrane-Inspired Evolutionary algorithm Based on artificial bee colony algorithm

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JOURNAL OF COMPUTATIONAL AND THEORETICAL NANOSCIENCE 2015年第7期12卷 1426-1433页

作者： Song, Xiaoxiao Wang, Jun Zhang, Bide Xihua Univ Sch Elect & Informat Engn Chengdu 610039 Sichuan Peoples R China

The paper presents a novel membrane-inspired evolutionary algorithm, named artificial bee colony algorithm based on P systems (ABCPS), which combines P systems and artificial bee colony algorithm (ABC). ABCPS uses the evolutionary rules of ABC, the one level membrane structure, and transformation or communication rules in P systems to design its algorithm. Experiments have been conducted on a set of 29 benchmark functions. The results demonstrate good performance of ABCPS in solving complex function optimization problems when compared with ABC.

关键词： artificial bee colony algorithm P Systems Function Optimization

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Community Detection in Complex Networks Using Improved artificial bee colony algorithm

Community Detection in Complex Networks Using Improved Artif...

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2016 International Conference on Communications, Information Management and Network Security (CIMNS2016)

作者： Ziyang Wang Xiaolin Zhao Peiyuan Wen Jingfeng Xue Changzhen Hu Beijing Key Laboratory of Software Security Engineering Technology Beijing Institute of Technology

ISBN: (纸本)9781510830981

With more and more various systems in nature and society are proved to be modeled as complex networks, community detection in complex networks as a fundamental problem becomes a hot research topic in a large scale of subjects. artificial bee colony algorithm(ABC) has high efficiency and does not require any prior knowledge about the number or the original division of the communities. So it is suitable to solve complex clustering problems. We propose an improved ABC algorithm which modifies the number of initial food sources and dynamically adjusts search scope. Experimental results show that our algorithm can discover communities effectively by the classic Zachary Karate Club network. By comparative experiments, the improved artificial bee colony algorithm outperforms the traditional ABC algorithm in complex network.

关键词： component complex network artificial bee colony algorithm community detection

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Optimization of a modified double-turbine Kalina cycle by using artificial bee colony algorithm

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APPLIED THERMAL ENGINEERING 2015年 91卷 19-32页

作者： Sadeghi, Sadegh Saffari, Hamid Bahadormanesh, Nikrouz Iran Univ Sci & Technol Sch Mech Engn Tehran Narmak Iran

Owing to appropriate performance of ammonia-water as a working fluid over two-phase region when exploiting low-temperature heat sources, a modified low-temperature double-turbine Kalina cycle system is designed to boost thermal efficiency. Due to low pressure after the second turbine, it is not affordable to use more than two turbines. Input mass flow rate of the second turbine is supplied by adding heat to the output liquid ammonia-water mixture from the first separator, separating the vapor at the outlet of the first turbine before blending the two streams. In order to reach the optimum thermal efficiency of the cycle, ABC (artificial bee colony) algorithm is implemented as a novel powerful multi-variable optimization algorithm. Considering the structure of the algorithm, convergence speed and accuracy of solutions have been considerably enhanced when compared to those of GA, PSO and DE algorithms. Such a relative enhancement is indicated by limit parameter and reducing probability of occurrence of local optimum problem. In this paper, thermal efficiency is selected as the objective function of ABC algorithm where its optimum value for the suggested Kalina cycle is found to be 26.32%. Finally, effects of the first separator inlet pressure and temperature, basic ammonia mass fraction and mass flow rate of the ammonia-water working fluid on net power output, required heat energy for the cycle and thermal efficiency are investigated. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Kalina cycle artificial bee colony algorithm Ammonia-water mixture Therthal efficiency

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An Improved artificial bee colony algorithm and Its Application to Multi-Objective Optimal Power Flow

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ENERGIES 2015年第4期8卷 2412-2437页

作者： He, Xuanhu Wang, Wei Jiang, Jiuchun Xu, Lijie Beijing JiaoTong Univ Natl Act Distribut Network Technol Res Ctr NANTEC Beijing 100044 Peoples R China

Optimal power flow (OPF) objective functions involve minimization of the total fuel costs of generating units, minimization of atmospheric pollutant emissions, minimization of active power losses and minimization of voltage deviations. In this paper, a fuzzy multi-objective OPF model is established by the fuzzy membership functions and the fuzzy satisfaction-maximizing method. The improved artificial bee colony (IABC) algorithm is applied to solve the model. In the IABC algorithm, the mutation and crossover operations of a differential evolution algorithm are utilized to generate new solutions to improve exploitation capacity;tent chaos mapping is utilized to generate initial swarms, reference mutation solutions and the reference dimensions of crossover operations to improve swarm diversity. The proposed method is applied to multi-objective OPF problems in IEEE 30-bus, IEEE 57-bus and IEEE 300-bus test systems. The results are compared with those obtained by other algorithms, which demonstrates the effectiveness and superiority of the IABC algorithm, and how the optimal scheme obtained by the proposed model can make systems more economical and stable.

关键词： optimal power flow fuzzy satisfaction-maximizing method artificial bee colony algorithm differential evolution algorithm tent chaos mapping

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On clarifying misconceptions when comparing variants of the artificial bee colony algorithm by offering a new implementation

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INFORMATION SCIENCES 2015年第0期291卷 115-127页

作者： Mernik, Marjan Liu, Shih-Hsi Karaboga, Dervis Crepinsek, Matej Univ Maribor Fac Elect Engn & Comp Sci SLO-2000 Maribor Slovenia Calif State Univ Fresno Dept Comp Sci Fresno CA 93740 USA Erciyes Univ Dept Comp Engn TR-38039 Kayseri Turkey

artificial bee colony (ABC) is a Swarm Intelligence algorithm that has obtained meta-heuristic researchers' attention and favor over recent years. It comprises good balance between exploitation (employed bee phase and onlooker bee phase) and exploration (scout bee phase). As nowadays, more researchers are using ABC and its variants as a control group to perform comparisons, it is crucial that comparisons with other algorithms are fair. This paper points to some misapprehensions when comparing meta-heuristic algorithms based on iterations (generations or cycles) with special emphasis on ABC. We hope that through our findings this paper can be treated as a beacon to remind researchers to learn from these mistakes. (C) 2014 Elsevier Inc. All rights reserved.

关键词： Swarm intelligence artificial bee colony algorithm Experiment replication

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Application of artificial bee colony algorithm on surface wave data

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COMPUTERS & GEOSCIENCES 2015年第Oct.期83卷 219-230页

作者： Song, Xianhai Gu, Hanming Tang, Li Zhao, Sutao Zhang, Xueqiang Li, Lei Huang, Jianquan China Univ Geosci Hubei Subsurface Multiscale Imaging Key Lab Inst Geophys & Geomat Wuhan 430074 Hubei Peoples R China

artificial bee colony (ABC) algorithm is applied to invert surface wave phase velocities. The ABC algorithm, one of swarm intelligence-based algorithms, is inspired from the particular intelligent foraging behavior of a honeybee swarm in nature. To facilitate convergence to an optimal solution, global exploration and local exploitation processes are carried out simultaneously in a robust ABC search process. Using synthetic and observed Rayleigh wave data, we examined the effectiveness and applicability of the ABC scheme in deducing an S-wave velocity profile for near-surface applications. Furthermore, we compared the performance of ABC to those of genetic algorithm (GA) and particle swarm optimization (PSO). We demonstrated that the ABC algorithm outperforms the standard binary-coded GA and the basic PSO, and it can be effectively used to interpret surface wave dispersion data with the great advantage of employing fewer control parameters. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： artificial bee colony algorithm Genetic algorithm Particle swarm optimization Surface waves Dispersion curves

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Chaotic artificial bee colony algorithm based solution of security and transient stability constrained optimal power flow

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2015年 64卷 136-147页

作者： Ayan, Kursat Kilic, Ulas Barakli, Burhan Sakarya Univ Dept Comp Engn Sakarya Turkey Celal Bayar Univ Dept Mechat Engn Manisa Turkey Sakarya Univ Dept Elect & Elect Engn Sakarya Turkey

Due to the increase rapidly of electricity demand and the deregulation of electricity markets, the energy networks are usually run close to their maximum capacity to transmit the needed power. Furthermore, the operators have to run the system to ensure its security and transient stability constraints under credible contingencies. Security and transient stability constrained optimal power flow (STSCOPF) problem can be illustrated as an extended OPF problem with additional line loading and rotor angle inequality constraints. This paper presents a new approach for STSCOPF solution by a chaotic artificial bee colony (CABC) algorithm based on chaos theory. The proposed algorithm is tested on IEEE 30-bus test system and New England 39-bus test system. The obtained results are compared to those obtained from previous studies in literature and the comparative results are given to show validity and effectiveness of proposed method. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： artificial bee colony algorithm Chaos theory Optimal power flow Security Transient stability

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