Bacterial foraging optimization algorithm: Theoretical foundations, analysis, and applications

Studies in Computational Intelligence

Volumn 203, Issue , 2009, Pages 23-55

  Das, Swagatam ^a   Biswas, Arijit ^a   Dasgupta, Sambarta ^a   Abraham, Ajith ^b  

^a JADAVPUR UNIVERSITY   (India)

^b NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Norway)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 65549143306     PISSN: 1860949X     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-01085-9_2     Document Type: Article

References (38)

1. Passino, K.M.: Biomimicry of Bacterial Foraging for Distributed Optimization and Control. IEEE Control Systems Magazine, 52-67 (2002)
2. Holland, J.H.: Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Harbor (1975)
3. Fogel, L.J., Owens, A.J., Walsh, M.J.: Artificial Intelligence through Simulated Evolution. John Wiley, Chichester (1966)
4. Rechenberg, I.: Evolutionsstrategie 1994. Frommann-Holzboog, Stuttgart (1994)
5. Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings of IEEE International Conference on Neural Networks, pp. 1942-1948 (1995)
6. Dorigo, M., Gambardella, L.M.: Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem. IEEE Transactions on Evolutionary Computation 1(1), 53-66 (1997)
7. Berg, H., Brown, D.: Chemotaxis in escherichia coli analysed by three-dimensional tracking. Nature 239, 500-504 (1972)
8. Berg, H.: Random Walks in Biology. Princeton Univ. Press, Princeton (1993)
9. Liu, Y., Passino, K.M.: Biomimicry of Social Foraging Bacteria for Distributed Optimization: Models, Principles, and Emergent Behaviors. Journal of Optimization Theory And Applications 115(3), 603-628 (2002)
10. Abramowitz, M., Stegun, I.A. (eds.): Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. Dover, New York (1972)
11. Bracewell, R.: Heaviside's Unit Step Function, H(x), The Fourier Transform and Its Applications, 3rd edn., pp. 57-61. McGraw-Hill, New York (1999)
12. Snyman, J.A.: Practical Mathematical Optimization: An Introduction to Basic Optimization Theory and Classical and New Gradient-Based Algorithms. Springer Publishing, Heidelberg (2005)
13. Dasgupta, S., Das, S., Abraham, A., Biswas, A.: Adaptive Computational Chemotaxis in Bacterial Foraging Optimization: An Analysis. IEEE Transactions on Evolutionary Computation (in press, 2009)
14. Abraham, A., Biswas, A., Dasgupta, S., Das, S.: Anaysis of Reproduction Operator in Bacterial Foraging Optimization. In: IEEE Congress on Evolutionary Computation CEC 2008, IEEE World Congress on Computational Intelligence, WCCI 2008, pp. 1476-1483. IEEE Press, USA (2008)
15. Murray, J.D.: Mathematical Biology. Springer, New York (1989)
16. Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence: From Natural to Artificial Systems. Oxford Univ. Press, New York (1999)
17. Okubo, A.: Dynamical aspects of Snimal grouping: swarms, schools, flocks, and herds. Advanced Biophysics 22, 1-94 (1986)
18. Wolpert, D.H., Macready, W.G.: No Free Lunch Theorems for Optimization. IEEE Transactions on Evolutionary Computation 1(1), 67-82 (1997)
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)
20. Biswas, A., Dasgupta, S., Das, S., Abraham, A.: Synergy of PSO and Bacterial Foraging Optimization: A Comparative Study on Numerical Benchmarks. In: Corchado, E., et al. (eds.) Second International Symposium on Hybrid Artificial Intelligent Systems (HAIS 2007), Innovations in Hybrid Intelligent Systems, ASC. Advances in Soft computing Series, vol. 44, pp. 255-263. Springer, Germany (2007)
21. Storn, R., Price, K.: Differential evolution - A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces. Journal of Global Optimization 11(4), 341-359 (1997)
22. Biswas, A., Dasgupta, S., Das, S., Abraham, A.: A Synergy of Differential Evolution and Bacterial Foraging Algorithm for Global Optimization. Neural Network World 17(6), 607-626 (2007)
23. Ulagammai, L., Vankatesh, P., Kannan, P.S., Padhy, N.P.: Application of Bacteria Foraging Technique Trained and Artificial and Wavelet Neural Networks in Load Forecasting. Neurocomputing, 2659-2667 (2007)
24. Munoz, M.A., Lopez, J.A., Caicedo, E.: Bacteria Foraging Optimization for Dynamical resource Allocation in a Multizone temperature Experimentation Platform. In: Anal. and Des. of Intel. Sys. using SC Tech., ASC, vol. 41, pp. 427-435 (2007)
25. Acharya, D.P., Panda, G., Mishra, S., Lakhshmi, Y.V.S.: Bacteria Foaging Based Independent Component Analysis. In: International Conference on Computational Intelligence and Multimedia Applications. IEEE Press, Los Alamitos (2007)
26. Chatterjee, A., Matsuno, F.: Bacteria Foraging Techniques for Solving EKF-Based SLAM Problems. In: Proc. International Control Conference (Control 2006), Glasgow, UK, August 30- September 01 (2006)
27. Tripathy, M., Mishra, S.: Bacteria Foraging-Based to Optimize Both Real Power Loss and Voltage Stability Limit. IEEE Transactions on Power Systems 22(1), 240-248 (2007)
28. Mishra, S., Bhende, C.N.: Bacterial Foraging Technique-Based Optimized Active Power Filter for Load Compensation. IEEE Transactions on Power Delivery 22(1), 457-465 (2007)
29. Mishra, S.: A hybrid least square-fuzzy bacterial foraging strategy for harmonic estimation. IEEE Trans. on Evolutionary Computation 9(1), 61-73 (2005)
30. Tang, W.J., Wu, Q.H., Saunders, J.R.: A Novel Model for Bacteria Foraging in Varying Environments. In: Gavrilova, M.L., Gervasi, O., Kumar, V., Tan, C.J.K., Taniar, D., Laganá, A., Mun, Y., Choo, H. (eds.) ICCSA 2006. LNCS, vol. 3980, pp. 556-565. Springer, Heidelberg (2006)
31. Biswas, A., Das, S., Dasgupta, S., Abraham, A.: Stability Analysis of the Reproduction Operator in Bacterial foraging Optimization. In: IEEE/ ACM International Conference on Soft Computing as Transdisciplinary Science and Technology (CSTST 2008), Paris, France, pp. 568-575. ACM Press, New York (2008)
32. Fernandes, C., Ramos, V., Agostinho, C.: Varying the Population Size of Artificial Foraging Swarms on Time Varying Landscapes. In: Duch, W., Kacprzyk, J., Oja, E., Zadrozny, S. (eds.) ICANN 2005. LNCS, vol. 3696, pp. 311-316. Springer, Heidelberg (2005)
33. Tripathy, M., Mishra, S., Lai, L.L., Zhang, Q.P.: Transmission Loss Reduction Based on FACTS and Bacteria Foraging Algorithm. In: PPSN, pp. 222-231 (2006)
34. Mishra, S., Bhende, C.N.: Bacterial Foraging Technique-Based Optimized Active Power Filter for Load Compensation. IEEE Transactions on Power Delivery 22(1), 457-465 (2007)
35. Kim, D.H., Cho, C.H.: Bacterial Foraging Based Neural Network Fuzzy Learning. In: IICAI 2005, pp. 2030-2036 (2005)
36. Dasgupta, S., Biswas, A., Das, S., Abraham, A.: Automatic Circle Detection on Images with an Adaptive Bacterial Foraging Algorithm. In: 2008 Genetic and Evolutionary Computation Conference, GECCO 2008, pp. 1695-1696. ACM Press, New York (2008)
37. Chen, H., Zhu, Y., Hu, K., He, X., Niu, B.: Cooperative Approaches to Bacterial Foraging Optimization. In: ICIC (2), pp. 541-548 (2008)
38. Wu, C., Zhang, N., Jiang, J., Yang, J., Liang, Y.: Improved Bacterial Foraging Algorithms and Their Applications to Job Shop Scheduling Problems. In: Beliczynski, B., Dzielinski, A., Iwanowski, M., Ribeiro, B. (eds.) ICANNGA 2007. LNCS, vol. 4431, pp. 562-569. Springer, Heidelberg (2007)