Abstract
This paper intends to incorporate a brain storming mechanism into the existing Teaching–Learning–Based Optimization (TLBO) algorithm. The potential solutions of TLBO evolve using the primitive steps that are maintained between the acts of teaching and learning. Another novel algorithm, Brain Storm Optimization (BSO) sticks to the philosophy of interchange of ideas by a team to develop as a whole. The brain storming methods from BSO are introduced into the working of TLBO and applied to a well–studied electric power dispatch problem of high intricacy. The results are compared to best of the existing solutions to demonstrate the efficacy of the proposed hybrid algorithm.
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References
Back, T., Fogel, D., Michalewicz, Z.: Handbook of evolutionary computation. Oxford University Press, New York (1997)
Bakirtzis, A., Petridis, V., Kazarlis, S.: Genetic algorithm solution to the economic dispatch problem. IEE Gen. Trans. Dist. 141(4), 377–382 (1994)
Gaing, Z.L.: Particle swarm optimization to solving the economic dispatch considering the generator constraints. IEEE Trans. on Power Syst. 18(3), 1187–1195 (2003)
Balamurugan, R., Subramanian, S.: Differential Evolution-based Dynamic Economic Dispatch of Generating Units with Valve-point Effects. Electric Power Components and Systems 36, 828–843 (2008)
Nayak, S.K., Krishnanand, K.R., Panigrahi, B.K., Rout, P.K.: Application of Artificial Bee Colony to Economic Load Dispatch Problem with Ramp Rate Limits and Prohibited Operating Zones. In: IEEE Proc. on Nature and Biologically Inspired Computing, pp. 1237–1242 (2009)
Krishnanand, K.R., Rout, P.K., Panigrahi, B.K., Mohapatra, A.: Solution to Non-convex Electric Power Dispatch Problem Using Seeker Optimization Algorithm. In: Panigrahi, B.K., Das, S., Suganthan, P.N., Dash, S.S. (eds.) SEMCCO 2010. LNCS, vol. 6466, pp. 537–544. Springer, Heidelberg (2010)
Attaviriyanupap, P., Kita, H., Tanaka, E., Hasegawa, J.: A hybrid EP and SQP for dynamic economic dispatch with nonsmooth fuel cost function. IEEE Trans. Power Syst. 17(2), 411–416 (2002)
Yuan, X., Wang, L., Yuan, Y., Zhang, Y., Cao, B., Yang, B.: A modified differential evolution approach for dynamic economic dispatch with valve-point effects. Energy Conversion and Management 49(12), 3447–3453 (2008)
Victoire, T.A.A., Jeyakumar, A.E.: A modified hybrid EP–SQP approach for dynamic dispatch with valve-point effect. Elect. Power and Energy Syst. 27(8), 594–601 (2005)
Victoire, T.A.A., Jeyakumar, A.E.: Deterministically guided PSO for dynamic dispatch considering valve-point effect. Elect. Power Syst. Res. 73(3), 313–322 (2005)
Victoire, T.A.A., Jeyakumar, A.E.: Reserve constrained dynamic dispatch of units with valve-point effects. IEEE Trans. on Power Syst. 20(3), 1273–1282 (2005)
Yuan, X., Su, A., Yuan, Y., Nie, H., Wang, L.: An improved PSO for dynamic load dispatch of generators with valve-point effects. Energy 34(1), 67–74 (2009)
Hemamalini, S., Simon, S.P.: Dynamic economic dispatch using artificial immune system for units with valve-point effect. Elect. Power and Energy Syst. 33(4), 868–874 (2011)
Pandi, V.R., Panigrahi, B.K.: Dynamic economic load dispatch using hybrid swarm intelligence based harmony search algorithm. Expert Syst. with Appl. 38(7), 8509–8514 (2011)
Rao, R.V., Savsani, V.J., Vakharia, D.P.: Teaching-learning-based optimization: A novel method for constrained mechanical design optimization problems. Computer-Aided Design 43(3), 303–315 (2011)
Krishnanand, K.R., Panigrahi, B.K., Rout, P.K., Mohapatra, A.: Application of Multi-Objective Teaching-Learning-Based Algorithm to an Economic Load Dispatch Problem with Incommensurable Objectives. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Satapathy, S.C. (eds.) SEMCCO 2011, Part I. LNCS, vol. 7076, pp. 697–705. Springer, Heidelberg (2011)
Shi, Y.: An Optimization Algorithm Based on Brainstorming Process. Int. J. of Swarm Intel. Res. 2(4), 35–62 (2011)
Osborn, A.F.: Applied imagination: Principles and procedures of creative problem solving. Charles Scribner’s Son, New York (1963)
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Ramanand, K.R., Krishnanand, K.R., Panigrahi, B.K., Mallick, M.K. (2012). Brain Storming Incorporated Teaching–Learning–Based Algorithm with Application to Electric Power Dispatch. In: Panigrahi, B.K., Das, S., Suganthan, P.N., Nanda, P.K. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2012. Lecture Notes in Computer Science, vol 7677. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35380-2_56
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DOI: https://doi.org/10.1007/978-3-642-35380-2_56
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