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Bacterial Foraging Optimization: A Survey

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Proceedings of the International Conference on Soft Computing for Problem Solving (SocProS 2011) December 20-22, 2011

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 130))

Abstract

Often real world provides some complex optimization problems that can not be easily dealt with available mathematical optimization methods. If the user is not very conscious about the exact solution of the problem in hand then intelligence emerged from social behavior of social colony members may be used to solve these kind of problems. Based on this concept, Passino proposed an optimization technique known as the bacterial foraging optimization algorithm (BFOA). The foraging behavior of bacteria produces an intelligent social behavior, called as swarm intelligence. Social foraging behavior of Escherichia coli is studied by researchers and developed a new algorithm named Bacterial foraging optimization algorithm (BFOA). BFOA is a widely accepted optimization algorithm and currently it is a growing field of research for distributed optimization and control. Since its inception, a lot of research has been carried out to make BFOA more and more efficient and to apply BFOA for different types of problems. This paper presents a review of BFOA modifications and it application areas.

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References

  1. Bakwad, K.M., Pattnaik, S.S., Sohi, B.S., Devi, S., Panigrahi, B.K., Gollapudi, S.V.: Bacterial foraging optimization technique cascaded with adaptive filter to enhance peak signal to noise ratio from single image. IETE Journal of Research 55(4), 173 (2009)

    Article  Google Scholar 

  2. Berg, H.C.: Motile behavior of bacteria. Physics Today 53(1), 24–30 (2000)

    Article  Google Scholar 

  3. Chatterjee, A., Fakhfakh, M., Siarry, P.: Design of second-generation current conveyors employing bacterial foraging optimization. Microelectronics Journal (2010)

    Google Scholar 

  4. Chen, H., Zhu, Y., Hu, K.: Self-adaptation in bacterial foraging optimization algorithm, vol. 1, pp. 1026–1031 (2008)

    Google Scholar 

  5. Chen, H., Zhu, Y., Hu, K.: Cooperative bacterial foraging optimization. Discrete Dynamics in Nature and Society, 1–17 (2009)

    Google Scholar 

  6. Chen, Y., Lin, W.: An improved bacterial foraging optimization, pp. 2057–2062 (2009)

    Google Scholar 

  7. Dang, J., Brabazon, A., O’Neill, M., Edelman, D.: Option model calibration using a bacterial foraging optimization algorithm, pp. 113–122 (2008)

    Google Scholar 

  8. Das, S., Biswas, A., Dasgupta, S., Abraham, A.: Bacterial foraging optimization algorithm: theoretical foundations, analysis, and applications. Foundations of Computational Intelligence 3, 23–55 (2009)

    Google Scholar 

  9. dos Santos Coelho, L., da Costa Silveira, C.: Improved bacterial foraging strategy for controller optimization applied to robotic manipulator system. In: 2006 IEEE Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control, pp. 1276–1281. IEEE (2006)

    Google Scholar 

  10. Eberhart, R.C., Shi, Y., Kennedy, J.: Swarm intelligence. Elsevier (2001)

    Google Scholar 

  11. Fogel, D.B.: Introduction to evolutionary computation. Evolutionary Computation: Basic Algorithms and Operators 1, 1 (2000)

    Google Scholar 

  12. Pang, H.-L., Wang, D.-W., Gao, Z.-W.: Adaptive bacterial foraging optimization and its application for bus scheduling. Journal of System Simulation 23(6), 1151–1155 (2011)

    Google Scholar 

  13. Gollapudi, S.V.R.S., Pattnaik, S.S., Bajpai, O.P., Devi, S., Vidya Sagar, C., Pradyumna, P.K., Bakwad, K.M.: Bacterial foraging optimization technique to calculate resonant frequency of rectangular microstrip antenna. International Journal of RF and Microwave Computer-Aided Engineering 18(4), 383–388 (2008)

    Article  Google Scholar 

  14. Hooshmand, R.A., Mohkami, H.: New optimal placement of capacitors and dispersed generators using bacterial foraging oriented by particle swarm optimization algorithm in distribution systems. Electrical Engineering (Archiv fur Elektrotechnik), 1–11

    Google Scholar 

  15. Hui, C., Yang, L.: Cbfo: The cooperative optimization of bacterial foraging. In: 2010 International Conference on Computer Application and System Modeling (ICCASM), vol. 2, pp. V2-106–V2-109. IEEE (2010)

    Google Scholar 

  16. Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings of IEEE International Conference on Neural Networks, vol. 4, pp. 1942–1948. IEEE (1995)

    Google Scholar 

  17. Abraham, A., Kim, D.H.: A hybrid genetic algorithm and bacterial foraging approach for global optimization and robust tuning of pid controller. SCI, vol. 75, pp. 171–199 (2007)

    Google Scholar 

  18. Kim, D.H.: Robust Tuning of Embedded Intelligent PID Controller for Induction Motor Using Bacterial Foraging Based Optimization. In: Wu, Z., Chen, C., Guo, M., Bu, J. (eds.) ICESS 2004. LNCS, vol. 3605, pp. 137–142. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  19. Kim, D.H., Abraham, A., Cho, J.H.: A hybrid genetic algorithm and bacterial foraging approach for global optimization. Information Sciences 177(18), 3918–3937 (2007)

    Article  Google Scholar 

  20. Kim, D.H., Cho, J.H.: Adaptive Tuning of PID Controller for Multivariable System Using Bacterial Foraging Based Optimization. In: Szczepaniak, P.S., Kacprzyk, J., Niewiadomski, A. (eds.) AWIC 2005. LNCS (LNAI), vol. 3528, pp. 231–235. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  21. Lin, W.X., Liu, P.X., Li, W.L., Chen, Y.H., Ou, C.: Application of bacterial foraging optimization in a non-linear model identification. Journal of System Simulation 24(10), 3100–3104 (2009)

    Google Scholar 

  22. Luo, Y., Li, J.: The controlling parameters tuning and its application of fractional order pid bacterial foraging-based oriented by particle swarm optimization, vol. 1, pp. 4–7 (2009)

    Google Scholar 

  23. Majhi, B., Panda, G., Choubey, A.: On the development of a new adaptive channel equalizer using bacterial foraging optimization technique. In: 2006 Annual IEEE India Conference, pp. 1–6. IEEE (2006)

    Google Scholar 

  24. Majhi, R., Panda, G., Majhi, B., Sahoo, G.: Efficient prediction of stock market indices using adaptive bacterial foraging optimization (abfo) and bfo based techniques. Expert Systems with Applications 36(6), 10097–10104 (2009)

    Article  Google Scholar 

  25. Abdillah, M., Soeprijanto, A., Mauridhi, H.P., Manuaba, I.B.G.: Coordination of pid based power system stabilizer and avr using combination bacterial foraging techique particle swarm optimization. In: 4th International Conference on Modeling, Simulation and Applied Optimization (2011)

    Google Scholar 

  26. Niu, B., Xiao, H., Tan, L., Li, L., Rao, J.: Modified Bacterial Foraging Optimizer for Liquidity Risk Portfolio Optimization. In: Li, K., Li, X., Ma, S., Irwin, G.W. (eds.) LSMS 2010. Communications in Computer and Information Science, vol. 98, pp. 16–22. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  27. Olesen, J.R., Hernandez, J.C., Zeng, Y.: Auto-Clustering Using Particle Swarm Optimization and Bacterial Foraging. In: Cao, L., Gorodetsky, V., Liu, J., Weiss, G., Yu, P.S. (eds.) ADMI 2009. LNCS, vol. 5680, pp. 69–83. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  28. Kou, P.-G., Zhou, J.-Z., He, Y.-Y., Xiang, X.-Q., Li, C.-S.: Optimal pid governor tuning of hydraulic turbine generators with bacterial foraging particle swarm optimization algorithm. In: Proceedings of the CSEE, vol. 26 (2009)

    Google Scholar 

  29. Sarasiri, N., Sujitjorn, S., Panikhom, S.: Hybrid bacterial foraging and tabu search optimization (btso) algorithms for lyapunov’s stability analysis of nonlinear systems. International Journal of Mathematics and Computers in Simulation 4(3), 81–89 (2010)

    Google Scholar 

  30. Passino, K.M.: Biomimicry of bacterial foraging for distributed optimization and control. IEEE Control Systems Magazine 22(3), 52–67 (2002)

    Article  MathSciNet  Google Scholar 

  31. Praveena, P., Vaisakh, K., Rama Mohana Rao, S.: Particle Swarm Optimization and Varying Chemotactic Step-Size Bacterial Foraging Optimization Algorithms Based Dynamic Economic Dispatch with Non-Smooth Fuel Cost Functions. In: Panigrahi, B.K., Das, S., Suganthan, P.N., Dash, S.S. (eds.) SEMCCO 2010. LNCS, vol. 6466, pp. 727–738. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  32. Price, K.V., Storn, R.M., Lampinen, J.: Differential evolution: a practical approach to global optimization. Springer, Heidelberg (2005)

    MATH  Google Scholar 

  33. Saber, A.Y., Venayagamoorthy, G.K.: Economic load dispatch using bacterial foraging technique with particle swarm optimization biased evolution. In: Swarm Intelligence Symposium, SIS 2008, pp. 1–8. IEEE (2008)

    Google Scholar 

  34. Sathya, P.D., Kayalvizhi, R.: Image segmentation using minimum cross entropy and bacterial foraging optimization algorithm

    Google Scholar 

  35. Shao, L., Chen, Y.: Bacterial foraging optimization algorithm integrating tabu search for motif discovery. In: 2009 IEEE International Conference on Bioinformatics and Biomedicine, pp. 415–418. IEEE (2009)

    Google Scholar 

  36. Su, T.J., Chen, L.W., Yu, C.J., Cheng, J.C.: Fuzzy pid controller design using self adaptive bacterial foraging optimization. In: Proceedings of SICE Annual Conference 2010, pp. 2604–2607. IEEE (2010)

    Google Scholar 

  37. Su, T.J., Cheng, J.C., Yu, C.J.: An adaptive channel equalizer using self-adaptation bacterial foraging optimization. Optics Communications 283(20), 3911–3916 (2010)

    Article  Google Scholar 

  38. Vaisakh, K., Praveena, P., Rao, S.R.M.: Pso-dv and bacterial foraging optimization based dynamic economic dispatch with non-smooth cost functions. In: 2009 International Conference on Advances in Computing, Control, and Telecommunication Technologies, pp. 135–139. IEEE (2009)

    Google Scholar 

  39. Wan, M., Li, L., Xiao, J., Wang, C., Yang, Y.: Data clustering using bacterial foraging optimization. Journal of Intelligent Information Systems, 1–21

    Google Scholar 

  40. Wang, Q., Gao, X.Z., Wang, C.: An adaptive bacterial foraging algorithm for constrained optimization

    Google Scholar 

  41. XiaoLong, L., RongJun, L., Ping, Y.: A bacterial foraging global optimization algorithm based on the particle swarm optimization, vol. 2, pp. 22–27

    Google Scholar 

  42. Yagmahan, B., Yenisey, M.M.: Ant colony optimization for multi-objective flow shop scheduling problem. Computers & Industrial Engineering 54(3), 411–420 (2008)

    Article  Google Scholar 

  43. Zang, T., He, Z., Ye, D.: Bacterial Foraging Optimization Algorithm with Particle Swarm Optimization Strategy for Distribution Network Reconfiguration. In: Tan, Y., Shi, Y., Tan, K.C. (eds.) ICSI 2010. LNCS, vol. 6145, pp. 365–372. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

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Authors and Affiliations

  1. ABV-Indian Institute of Information Technology and Management, Gwalior, India

    Vivek Agrawal, Harish Sharma & Jagdish Chand Bansal

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  1. Vivek Agrawal
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  2. Harish Sharma
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  3. Jagdish Chand Bansal
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Correspondence to Vivek Agrawal .

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Editors and Affiliations

  1. , Department of Mathematics, Indian Institute of Technology Roorkee, Uttarakhand, Roorkee, 247667, India

    Kusum Deep

  2. Department of Mathematics and, Computer Science, Liverpool Hope University, Hope Park, Liverpool, L16 9JD, United Kingdom

    Atulya Nagar

  3. , Department of Paper Technology, Indian Institute of Technology Roorkee, Uttarakhand, Roorkee, 247667, India

    Millie Pant

  4. Information Technology and Management, ABV-Indian Institute of, 109, E- Block, Gwalior, 474010, India

    Jagdish Chand Bansal

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Agrawal, V., Sharma, H., Bansal, J.C. (2012). Bacterial Foraging Optimization: A Survey. In: Deep, K., Nagar, A., Pant, M., Bansal, J. (eds) Proceedings of the International Conference on Soft Computing for Problem Solving (SocProS 2011) December 20-22, 2011. Advances in Intelligent and Soft Computing, vol 130. Springer, India. https://doi.org/10.1007/978-81-322-0487-9_23

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  • DOI: https://doi.org/10.1007/978-81-322-0487-9_23

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