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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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Integrated bacteria foraging algorithm for cellular manufacturing in supply chain considering facility transfer and production planning

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APPLIED SOFT COMPUTING 2018年 62卷 602-618页

作者： Liu, Chunfeng Wang, Jufeng Leung, Joseph Y. -T. Hangzhou Dianzi Univ Sch Management Hangzhou 310018 Zhejiang Peoples R China China Jiliang Univ Dept Math Hangzhou 310018 Zhejiang Peoples R China New Jersey Inst Technol Dept Comp Sci Newark NJ 07102 USA

This paper presents an integrated model of facility transfer and production planning in dynamic cellular manufacturing based supply chain. On one hand, transferring facilities to the factory with large order scan facilitate the distribution of products to the local customer zone and responds to the order demand rapidly but will generate transfer cost. Moreover, when many sets of facilities are transferred to certain factory where a lot of product types are produced, the selection of supplier(s) with low material cost will become difficult from the viewpoint of the entire supply chain. On the other hand, due to the limited production capacity and the dynamic of market demands, late delivery or production in advance is often applied during each period. This method will result in backorder cost or holding cost of inventory although it can smooth the production loads. To minimize the total operation cost, we propose a novel integrated bacteria foraging algorithm (IBFA) embedding a five-phase based heuristic (FPBH). The experiment is conducted to verify the performances of the IBFA, modified bacteria evolution operators and the FPBH. The computational results indicate that: (1) with the modified operators and the FPBH, the IBFA performs better than without them, and (2) the IBFA often outperforms the heuristic based genetic algorithm and heuristic based simulated annealing within the same runtime. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Cellular manufacturing system Facility transfer Production planning Supply chain bacteria foraging algorithm Heuristic

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On-line Optimization of Energy-saving Train Control using bacteria foraging algorithm 18

On-line Optimization of Energy-saving Train Control using Ba...

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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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Optimal Controller Design for AGC with Battery Energy Storage Using bacteria foraging algorithm

Optimal Controller Design for AGC with Battery Energy Storag...

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2017 IEEE Power & Energy Society General Meeting

作者： Xie, Pingping Zhu, Jizhong Xuan, Peizheng China Southern Power Grid Elect Power Res Inst Guangzhou Guangdong Peoples R China

ISBN: (纸本)9781538622124

The battery energy storage (BES) is very promising to be used for improving the performance of automatic generation control (AGC) in power system by offering fast active power compensation. However, the improper parameters of controller in AGC system may cause an unstable frequency problem. This paper presents an optimal controller design method based on bacteria foraging algorithm (BFA) for AGC system with BES. A two-area reheat thermal system is considered to be equipped with the proportional plus integral (PI) controllers. The BFA technique is employed to search for the optimum controller parameters by minimizing the integral of time multiply absolute error (ITAE) index. The performance of the proposed BFA tuning controller has been evaluated with that of the controllers tuned by particle swarm optimization (PSO) and genetic algorithm (GA). Simulation results emphasize the performance of AGC system with BES and demonstrate the superiority of the proposed BFA tuning controller compared to the optimized controller based on PSO and GA.

关键词： Automatic generation control bacteria foraging algorithm battery energy storage controller design

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Worker assignment and production planning with learning and forgetting in manufacturing cells by hybrid bacteria foraging algorithm

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COMPUTERS & INDUSTRIAL ENGINEERING 2016年 96卷 162-179页

作者： Liu, Chunfeng Wang, Jufeng Leung, Joseph Y-T Hangzhou Dianzi Univ Sch Management Hangzhou 310018 Peoples R China China Jiliang Univ Dept Math Hangzhou 310018 Peoples R China New Jersey Inst Technol Dept Comp Sci Newark NJ 07102 USA Hefei Univ Technol Sch Management Hefei 230009 Peoples R China

We consider a joint decision model of worker assignment and production planning in a dynamic cellular manufacturing system of fiber connector manufacturing industry. On one hand, due to the learning and forgetting effects of workers, the production rate of each workstation will often change. Thus, the bottleneck workstation may transfer to another one in the next period. It is worthwhile to reassign multi-skilled workers such that the production rate of bottleneck workstation may increase. On the other hand, because of the limited production capacity and variety of orders, late delivery or production in advance often occurs at each period. The parts with operational sequence need to be dispatched to the desirable cells for processing. The objective is to minimize backorder cost and holding cost of inventory. To solve this complicated problem, we propose an efficient hybrid bacteria foraging algorithm (HBFA) with elaborately designed solution representation and bacteria evolution operators. A two-phase based heuristic is embedded in the HBFA to generate a high quality initial solution for further search. We tested our algorithm using randomly generated instances by comparing with the original bacteria foraging algorithm (OBFA), discrete bacteria foraging algorithm (DBFA), hybrid genetic algorithm (HGA) and hybrid simulated annealing (HSA). Our results show that the proposed HBFA has better performance than the four compared algorithms with the same running time. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Cellular manufacturing system Worker assignment Production planning bacteria foraging algorithm Learning and forgetting Operation sequence

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Solving cell formation and task scheduling in cellular manufacturing system by discrete bacteria foraging algorithm

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2016年第3期54卷 923-944页

作者： Liu, Chunfeng Wang, Jufeng Leung, Joseph Y. -T. Li, Kai Hangzhou Dianzi Univ Sch Management Hangzhou Zhejiang Peoples R China China Jiliang Univ Dept Math Hangzhou 310018 Zhejiang Peoples R China New Jersey Inst Technol Dept Comp Sci Newark NJ 07102 USA Hefei Univ Technol Sch Management Hefei Peoples R China

We consider a joint decision model of cell formation and task scheduling in cellular manufacturing system under dual-resource constrained (DRC) setting. On one hand, machines and workers are multi-functional and/or multi-skilled, and they are grouped into workstations and cells. On the other hand, there is a processing sequence among operations of the parts which needs to be dispatched to the desirable workstations for processing. Inter-cell movements of parts can reduce the processing times and the makespan but will increase the inter-cell material handling costs. The objective of the problem is to minimise the material handling costs as well as the fixed and operating costs of machines and workers. Due to the NP-hardness of the problem, we propose an efficient discrete bacteria foraging algorithm (DBFA) with elaborately designed solution representation and bacteria evolution operators to solve the proposed problem. We tested our algorithm using randomly generated instances with different sizes and settings by comparing with the original bacteria foraging algorithm and a genetic algorithm. Our results show that the proposed DBFA has better performance than the two compared algorithms with the same running time.

关键词： group scheduling bacteria foraging algorithm operation sequence cell formation cellular manufacturing system

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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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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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Coordinated tuning of PSS and TCSC to improve Hopf Bifurcation margin in multimachine power system by a modified bacteria foraging algorithm

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2015年第Mar.期66卷 97-109页

作者： Tripathy, M. Mishra, S. Veer Surendra Sai Univ Technol Dept Elect Engn Burla Odisha India IIT Delhi Dept Elect Engn New Delhi India

Recent research works have reported the effects of rotor angle dynamics of generators on bifurcation related system instability. This study intends to verify the possible influence of the Power System Stabilizers (PSS) and the Thyristor Controlled Series Capacitors (TCSC), on instabilities related to the Hopf Bifurcation (HB). Recently proposed optimization algorithm known as bacteria foraging algorithm (BFA) in its modified version is applied in this study to tune the controller parameters of nine numbers of PSS and two numbers of TCSC present in the 10 machine New England power system. The main objective of this work is to maximize the margin of loading in the same system before the occurrence of the HB. Moreover, the formulation of a properly designed objective function is also an important issue that affects the final result. The objective function, that is formulated only to improve the overall damping in power system, may not be sufficient to avoid the HE under stressed operating condition. Therefore, this study proposes to reformulate an eigenvalue based objective function to improve the extent of loading before the HB could occur in the system. A coordinated control of the TCSC with those of the PSS may enable the controllers to delay the point of HE, compared to the case when the PSS alone were operating in the system. At the outset, the control parameter settings of several transformer taps and PV-bus voltages of nine generators were optimized to improve the steady state Voltage Stability Limit (VSL) of the system. At these settings, the damping controller parameters are tuned to improve the loadability before the point of HB. Similar approach is adopted when the TCSCs were operating coordinately with the PSS. At the end, small perturbation cases were simulated in the system to verify the performance of designed controllers in time domain analysis. The results further establish the efficacy of the controllers (C) 2014 Elsevier Ltd. All rights reserved.

关键词： TCSC PSS bacteria foraging algorithm Hopf Bifurcation Notch point Voltage Stability Limit

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