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World Congress on Nature and Biologically Inspired Computing

作者： Tripathy, M. Barisal, A. K. Veer Surendra Sai Univ Technol Dept Elect Engg Sambalpur Orissa India

ISBN: (纸本)9781424450534

This paper presents new optimization approach involving a modified bacteria foraging algorithm (BFA) applied to economic load dispatch involving wind energy conversion systems (WECS). The approach utilizes the natural selection of global optimum bacterium having successful foraging strategies in the cost function including the factors of overestimation and underestimation of available wind energy According to the stochastic nature of wind speed characteristics based on Weibull probability density function, the optimization problem is numerically solved for a scenario involving three conventional and two wind-powered generators. The simulation results provide optimal solutions of scheduling of generators under the risk of over estimation and underestimation of available wind power.

关键词： bacteria foraging algorithm Economic dispatch Weibullprobability densityfunction Wind energy

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Optimal power flow solution of wind integrated power system using modified bacteria foraging algorithm

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2014年第Jan.期54卷 306-314页

作者： Panda, Ambarish Tripathy, M. Veer Surendra Sai Univ Technol Dept Elect Engn Burla Odisha India

Owing to the intermittent nature of wind flow, optimal power flow in a power system with considerable wind energy penetration is a challenging issue. In this paper an OFF solution is proposed for IEEE 30 bus power system modified by replacing three conventional generators with equivalent wind energy conversion systems (WECS). The uncertain nature of wind power has the risk of over or under estimating the capacity of available wind power. This uncertainty has been suitably modeled and included in the OPF framework. Moreover, to justify the limitation of reactive power generation capability of doubly fed induction generator based WECS during under estimation, additional cost component corresponding to external reactive power (Q) generating sources has been added in the objective function. The scheduling problem of WECS integrated power system is solved by formulating it as an optimization problem. Genetic algorithm and a modified bacteria foraging algorithm are employed separately to determine the optimal schedule. The optimal solution obtained with a modified version of BFA has been found to give better results compared to GA. The results depict the impact of wind and thermal scheduling on total system cost and reiterate the need of additional support of reactive power resources to maintain stable voltage profiles of the wind-thermal system. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Optimal power flow Wind energy conversion system bacteria foraging algorithm Doubly fed induction generator

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Application of bacteria foraging algorithm in Designing Log Periodic Dipole Array for Entire UHF TV Spectrum

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INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING 2013年第2期23卷 157-171页

作者： Mangaraj, Biswa Binayak Misra, Iti Saha Sanyal, Salil K. Veer Surendra Sai Univ Technol Dept Elect & Telecommun Engn Sambalpur 768018 Orissa India Jadavpur Univ Dept Elect & Telecommun Engn Kolkata 700032 W Bengal India

In this article, an attempt has been made to revisit the design of well-established log periodic dipole array (LPDA) in light of recent optimization technique, the bacteria foraging algorithm (BFA). Although there are many works published in the literatures based on various optimization techniques, this article deals with the optimization of the LPDA for the entire ultra high frequency (UHF) television (TV) spectrum (470-870 MHz) covering 400 MHz bandwidth and accommodating 49 channels. The challenges of this design lie in selecting suitable values of tau and sigma for 134 frequency points for which different sets of all the output parameters such as gain, input impedance (Z(in)), front-to-back ratio (FTBR), first side lobe level (FSLL), voltage standing wave ratio (VSWR), and so forth are obtained and then averaged over to get Gain(av), Z(inAav), FTBRav, FSLLav, and VSWRav close to the desired values. These average values are used to design suitable fitness function. Another important aspect of this article is to provide exhaustive design details for LPDA using network theory that would couple to the BFA for getting the optimized number of elements to satisfy the desired values of Z(inav), Gain(av), FTBRav, FSLLav, and VSWRav, set as 50 Omega, 9 dBi, 40 dB, 40 dB, and 1.1, respectively. Moreover, this LPDA design considers the standard wire gauge dipole elements, which is just a very practical approach in the design procedure. (C) 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE 23: 157-171, 2013.

关键词： log periodic dipole array design UHF TV spectrum bacteria foraging algorithm fitness function optimization standard wire gauge

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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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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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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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A bacteria foraging algorithm based cell formation considering operation time

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JOURNAL OF MANUFACTURING SYSTEMS 2012年第3期31卷 326-336页

作者： Nouri, Hossein Hong, Tang Sai Islamic Azad Univ Sanandaj Branch Fac Engn Sanandaj Iran Univ Putra Malaysia Fac Engn Serdang 43400 Selangor Darul Malaysia

The cellular manufacturing system (CMS) is considered as an efficient production strategy for batch type production. The CMS relies on the principle of grouping machines into machine cells and machine parts into part families based on pertinent similarity measures. The bacteria foraging algorithm (BFA) is a new in development computation technique extracted from the social foraging behavior Escherichia coli (E. coli) bacteria. Ever since Kevin M. Passino invented the BFA, one of the main challenges has been employment of the algorithm to problem areas other than those for which the algorithm was proposed. This research work inquires the first applications of this emerging novel optimization algorithm to the cell formation (CF) problem. In addition, a newly developed BFA-based optimization algorithm for CF is discussed. In this paper, an attempt is made to solve the cell formation problem meanwhile taking into consideration number of voids in cells and a number of exceptional elements based on operational time of the parts required for processing in the machines. The BFA is suggested to create machine cells and part families. The performance of the proposed algorithm is compared with a number of algorithms that are most commonly used and reported in the corresponding scientific literature such as similarity coefficients methods (SCM), rank order clustering (ROC), ZODIAC, GRAFICS, MST, GATSP, GP, K-harmonic clustering (KHM), K-means clustering, C-link clustering, modified ART], GA (genetic algorithm), evolutionary algorithm (EA), and simulated annealing (SA) using defined performance measures known as modified grouping efficiency and grouping efficacy. The results lie in favor of better performance of the proposed algorithm. (C) 2012 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.

关键词： Cell formation Operation time bacteria foraging algorithm

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Application of bacteria foraging algorithm for the Design Optimization of Multi-Objective Yagi-Uda Array

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INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING 2011年第1期21卷 25-35页

作者： Mangaraj, B. B. Misra, I. S. Sanyal, S. K. Jadavpur Univ Dept Elect & Telecommun Engn Kolkata 700032 India Veer Surendrasai Univ Technol Dept Elect & Telecommun Engn Burla 768018 Sambalpur India

The design of antenna array with desirable multiple performance parameters such as directivity, input impedance, beam width, and side-lobe level using any optimization algorithm is a highly challenging task. bacteria foraging algorithm (BFA), as reported by electrical engineers, is the most robust and efficient algorithm in comparison with other presently available algorithms for global optimization of multi-objective, multi-parameter design problems. The objective of this article is to apply this new optimization technique, BFA, in the design of Yagi-Uda array for multi-objective design parameters. We optimize length and spacing for 6 and 15 elements array to achieve higher directivity, pertinent input impedance, minimum 3-dB beam width, and maximum front to back ratio both in the E and H planes of the array. At first, we develop a Method of Moments code in MATLAB environment for the Yagi-Uda array structure for obtaining the above design parameters and then coupled with the BFA for the evaluation of the optimized design parameters. Detail simulation results are included to confirm the design criteria. (C) 2010 Wiley Periodicals, Inc. Int J RF and Microwave CAE 21:25-35, 2011.

关键词： bacteria foraging algorithm fitness function moment method multi-objective function Yagi-Uda array

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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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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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