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2nd International Conference on algorithms, Computing and Systems (ICACS)

作者： Xiao, Si-yu Liu, Jiang Cai, Bai-gen Beijing Jiaotong Univ Sch Elect & Informat Engn Beijing 100044 Peoples R China Beijing Jiaotong Univ Sch Comp & Informat Technol Beijing 100044 Peoples R China

ISBN: (纸本)9781450365093

Reducing the energy consumption has been a significant issue in urban transit operations. Considering the prior constraint from the operational schedule, the online optimization of the speed curve between successive stations is capable of improving the energy saving capability and enhancing cost-efficiency of the whole rail transit system. To fulfill the requirements of schedule adherence, an on-line optimization method for reducing energy consumption the train traction control operation is presented in this paper. In this method, the bacteria foraging algorithm is adopted to achieve an optimal solution of an objective function concerning the energy consumption and other related factors, with which the speed curve for the following rail section can be updated and adjusted in-time to cope with the possible deviation between time schedule and the practical operation. With the integration of the rail dispatching and train operation control, the control strategy of the train can be updated according to specifically modified trip plan, which means that the changed schedule for the following rail section still can be fulfilled by re-calculating the optimized speed curve of the train within the standing time in a station. The optimization is achieved under a multi-objective optimization framework, where the energy consumption and passenger comfort degree are concerned under a time-domain constraint that might be adjusted based on the latest schedule. Results from simulation demonstrate the effectiveness and feasibility of the proposed method, which illustrate the great potentials in safer and greener urban transit systems in the future.

关键词： Energy saving train traction control online optimization bacteria foraging algorithm

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Time Frequency Analysis and Classification of Power Quality Events Using bacteria foraging algorithm 1

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1st International Conference on Computational Intelligence in Data Mining (ICCIDM)

作者： Jagadeesh, S. Biswal, B. GMR Inst Technol Dept ECE Rajam 532127 Andhra Pradesh India

ISBN: (纸本)9788132222026;9788132222019

This paper proposes a novel method Modified Hilbert Huang Transform which is the combination of empirical-mode decomposition (EMD) and Hilbert transform with an equivalent window for Time frequency analysis. Initially the Non-stationary power signal is decomposed using EMD to get Intrinsic Mode functions (IMFs) and then Hilbert transform with an equivalent window is applied to all the IMFs to obtain instantaneous amplitude and frequency for Modified Hilbert Energy Spectrum. Different features are extracted from the Modified Hilbert Energy Spectrum and these features are applied to the bacteria foraging algorithm for automatic classification.

关键词： Non-stationary power signals EMD (Empirical mode decomposition) Modified Hilbert Huang transform (MHHT) bacteria foraging algorithm

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The bacteria foraging algorithm for global optimization based on pheromone 12

The bacteria foraging algorithm for global optimization base...

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2015 12th International Conference on Service Systems and Service Management (ICSSSM)

作者： Liu, Xiaolong Huang, Lingli Chang, Xianying South China Univ Technol Sch Business Adm Guangzhou Guangdong Peoples R China

ISBN: (纸本)9781479983285

In view of the defect that the migration operator randomness is too strong to reduce the bacteria overall fitness, but not conducive to the overall optimization when bacteria foraging algorithm is in the optimization process. Then the pheromone of ant colony algorithm is introduced into the bacteria foraging algorithm. Through the migration of maximum pheromone and smaller pheromone, this paper improves the convergence precision, the global convergence ability of the original algorithm and establishes the hybrid bacteria foraging optimization algorithm. Meanwhile, the Cauchy variation is introduced in reproduction operation in order to enhance the global searching ability of algorithm. Then the paper adopts high dimensional complex standard functions to test these three kinds of bionic algorithms. The results indicate that the new algorithm significantly improves the search speed, partly avoids the local convergence problem and is more suitable for solving optimization problems of complex high dimensional engineering.

关键词： Pheromone Cauchy variation bacteria foraging algorithm

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Performance evaluation of two popular antennas designed using a bacteria foraging algorithm

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ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH 2016年第4期19卷 1788-1800页

作者： Mangaraj, Biswa Binayak Mohanty, Saumendra Kumar Hota, Satyabrat Veer Surendra Sai Univ Technol Dept Elect & Telecommun Engn Burla 768018 Sambalpur India SOA Univ Inst Tech Educ & Res Dept Elect & Instrumentat Engn Bhubaneswar 751030 Orissa India

Two popular antennas such as the Yagi-Uda Array (YUA) and the Log Periodic Dipole Array (LPDA) with the same number of dipole elements are optimally designed using bacteria foraging algorithm (BFA). BFA being one of the successful optimization algorithms, used to optimize many design parameters of these two antennas to get a number of desired performance parameters. A YUA is designed here, mainly to realize high directivity, input-impedance (Z(in)) close to 50 Omega, high Front To Back Ratio (FTBR), high Front-tomaximum-Side-Lobe-Level (FSLL), low Half Power Beam Width (HPBW), and appreciable bandwidth, whereas a LPDA is designed here, mainly to achieve high bandwidth, average Z(in) close to 50 Omega, high average FTBR, high average FSLL, low average HPBW, and appreciable average directivity. The successful design approaches, application and comparative study of these two antennas presented here can also be extended to other antennas. (C) 2016 Karabuk University. Publishing services by Elsevier B.V.

关键词： bacteria foraging algorithm Design parameters Fitness function Log Periodic Dipole Array Optimization Performance parameters Yagi-Uda Array

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Hybrid bacteria foraging algorithm With PSO and DE algorithm for Optimal Cluster Head Selection in Wireless Sensor Networks

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INTERNATIONAL JOURNAL OF COGNITIVE INFORMATICS AND NATURAL INTELLIGENCE 2022年第1期16卷

作者： Bose, Pitchaimanickam Kalasalingam Acad Res & Educ Krishnankoil Tamil Nadu India

Network lifetime and energy constraint are the main issues for the application of wireless sensor networks. Sensor nodes spend more energy in the communication process and affect the network lifetime. Clustering is the technique for choosing the optimal cluster head from the clusters. LEACH- C is the clustering protocol in WSN. BFA is applied in the LEACH-C protocol to form the optimal clusters. This optimization obtains more steps in the tumbling process and reaches the global optimum solution very slowly. This method directly affects the network lifetime. The above limitations are overcome by introducing the hybrid approach of bacteria foraging algorithm by integrating the PSO, and DE is applied in LEACH-C algorithm for finding the optimal cluster head. The best foraging solution is utilized in the chemotactic behavior of the bacterium by using PSO and DE algorithms. The proposed methodology increases by 66% and 77% of the alive nodes when compared to FA and BFPSO.

关键词： Alive Nodes bacteria foraging algorithm Clustering Differential Evolution Energy Consumption Network Lifetime Particle Swarm Optimization Wireless Sensor Networks

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Efficiency and economic optimization of shell and tube heat exchanger using bacteria foraging algorithm

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SN APPLIED SCIENCES 2020年第1期2卷 13页

作者： Sai, Juluru Pavanu Rao, B. Nageswara Vignans Fdn Sci Technol & Res Dept Mech Engn Guntur 522213 Andhra Pradesh India

Shell and tube heat exchanger (STHE) is widely used in the industries for various purposes due to its capacity to withstand pressure. STHE has the drawback of more cost and lower efficiency. Many existing methods involve in applying the optimization technique to decrease the cost of the system. Existing method has the lower efficiency in the optimization due to the random initialization and poor convergence. This research applies the bacteria foraging algorithm (BFA) to increase the efficiency and decrease the cost of the STHE system. The BFA has the advantages of the faster convergence and the global search approach to increase the performance in design. The proposed BFA is evaluated in the two case studies and compared with the existing method. The proposed BFA in multi-objective optimization of STHE has the total cost of 41,464 (sic), while existing method has the total cost of 41,913 (sic).The proposed BFA method also achieved high heat efficiency coefficient of 1089, and the existing method has 1031.47.

关键词： bacteria foraging algorithm Faster convergence Global search approach Shell and tube heat exchanger

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A Comparative Study of Optimization Techniques in Adaptive Antenna Array Processing: The bacteria-foraging algorithm and Particle-Swarm Optimization

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IEEE ANTENNAS AND PROPAGATION MAGAZINE 2009年第6期51卷 69-81页

作者： Datta, Tanumay Misra, Iti Saha Jadavpur Univ Dept Elect & Telecommun Engn Kolkata 700032 India

This paper presents a comparative study between the bacteria-foraging (BF) and Particle-Swarm Optimization (PSO) algorithms, and their application to the antenna-array optimization problem. The performance of the bacteria-foraging algorithm is studied by varying its different parameters in beamforming and null-steering problems. Null steering along with sidelobe suppression is also done for various degrees of complexity. A generic cost function is developed, the parameters of which can be controlled to meet the requirements of the particular application. The two algorithms are compared for null depth, average sidelobe level, and rate of convergence for different numbers of interference signals. The performance of these methods are compared for output noise power for the same noise inputs. Results are shown for a linear dipole antenna-array system.

关键词： Optimization methods bacteria foraging algorithm particle swarm optimization adaptive arrays antenna arrays array signal processing null steering dipole arrays

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bacteria foraging Optimization algorithm for Robotic Cell Scheduling Problem

Bacteria Foraging Optimization Algorithm for Robotic Cell Sc...

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5th International Conference on Materials Processing and Characterization (ICMPC)

作者： Majumder, Arindam Laha, Dipak Natl Inst Technol Agartala Dept Mech Engn Tripura W India Jadavpur Univ Dept Mech Engn Kolkata India

The present study deals with the application of BFO for solving robotic cell problem. One of the major disadvantages of Passino invented BFO is its applicability constrains for solving problems except those contain continuous domain. Thus to make BFO applicable in robotic cell problem, Pairwise interchange mutation is chosen for tumbling and swimming operation during chemotaxis. While cyclic-shift neighbourhood mutation is used for random movement duringElimination-Dispersal. The example related to the two-machine robotic cell scheduling problem with sequence-dependent setup times (2RCSDST) was used to demonstrate the performance of the proposed discrete bacteria foraging algorithm. Large part sized problems varying from 200 to 500 part size was considered during this study. The computational results thus obtained were compared with two other existing optimization techniques and found BFO as the better performer to solve such large sized problems. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Scheduling 2-machine centered robot cell total cycle time bacteria foraging algorithm minimal part set sequence sequence of robot moves

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Multi-colony bacteria foraging optimization with cell-to-cell communication for RFID network planning

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APPLIED SOFT COMPUTING 2010年第2期10卷 539-547页

作者： Chen, Hanning Zhu, Yunlong Hu, Kunyuan Chinese Acad Sci Shenyang Inst Automat Key Lab Ind Informat Fac Off 3 Shenyang 110016 Peoples R China

In order to obtain accurate and reliable network planning in the Radio Frequency Identification (RFID) communication system, the locations of readers and the associated values for each of the reader parameters have to be determined. All these choices must optimize a set of objectives, such as tag coverage, economic efficiency, load balance, and interference level between readers. This paper proposes a novel optimization algorithm, namely the multi-colony bacteria foraging optimization (MC-BFO), to solve complex RFID network planning problem. The main idea of MC-BFO is to extend the single population bacterial foraging algorithm to the interacting multi- colony model by relating the chemotactic behavior of single bacterial cell to the cell-to-cell communication of bacterial community. With this multi- colony cooperative approach, a suitable diversity in the whole bacterial community can be maintained. At the same time, the cell-to-cell communication mechanism significantly speeds up the bacterial community to converge to the global optimum. Then a mathematical model for planning RFID networks is developed based on the proposed MC-BFO. The performance of MC-BFO is compared to both GA and PSO on RFID network planning problem, demonstrating its superiority. (C) 2009 Elsevier B.V. All rights reserved.

关键词： RFID network planning bacteria foraging algorithm MC-BFO GA PSO

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Automatic Generation Control in an Interconnected Power System Incorporating Diverse Source Power Plants Using bacteria foraging Optimization Technique

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2015年第2期43卷 189-199页

作者： Nasiruddin, Ibraheem Bhatti, Terlochan S. Hakimuddin, Nizamuddin Qassim Univ Dept Elect Engn Buraydah Saudi Arabia Indian Inst Technol Delhi Ctr Energy Studies New Delhi India New Okhla Ind Dev Author Div EM 2 Noida Uttar Pradesh India

This article presents automatic generation control (AGC) of a two-area interconnected power system with diverse energy sources using the bacteria foraging optimization technique. The control areas of interconnected power systems consist of hydro, thermal, and gas power plants. In this study, the proportional-integral-derivative (PID) structures of AGC regulators are designed for various case studies identified herein. An artificial intelligent optimization algorithm using the modeling behavior of E. Coli bacteria present in human intestines, is applied to tune the gains of PID structured AGC regulators. The closed-loop system dynamic response plots are obtained with designed AGC regulators for various power system models. The effectiveness of the proposed AGC regulators is demonstrated in the wake of a 1% step load disturbance in one of the control areas. It has been shown that the system dynamic responses subject to a step load disturbance are superior over other power plant combinations in a control area with only thermal and gas power plants participating in the AGC schemes, and it is sluggish/poor when only hydro power plants participated in the AGC scheme as one of the diverse sources in the power system.

关键词： bacteria foraging algorithm diverse source power plants integral square error interconnected power system automatic generation control

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