Abstract
Optimization problems of thermal systems are multi-model, multi-dimensional, nonlinear, and implicit in nature. Analytical methods are not suitable to optimize such thermal systems as these methods trap into a local optimum. Metaheuristic techniques are often considered as the best choice for the optimization of such thermal systems . A large number of metaheuristics have been developed and used significantly since last two decades. These metaheuristics have proved their effectiveness to solve many real and challenging practical optimization problems. Eleven different metaheuristic algorithms are described in this chapter in detail with their pseudo code . These algorithms are further used to optimize the various thermal systems , which are discussed in subsequent chapters. The MATLAB code of these algorithms is also given in this book.
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References
Cheng M.Y., Prayogo D. (2014) ‘Symbiotic Organisms Search: A new metaheuristic optimization algorithm’, Computers & Structures, vol. 139, 98–112.
Holland J. (1975) Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor.
Karaboga, D. (2005) An idea based on honey bee swarm for numerical optimization, Technical Report TR06, Computer Engineering Department, Erciyes University, Turkey, 2005.
Karaboga, D. Basturk, B. (2007a) A powerful and efficient algorithm for numerical function optimization: artificial bee colony algorithm, Journal of Global Optimization 39, 45–47.
Karaboga, D. Basturk, B. (2007b) Artificial bee colony (ABC) optimization algorithm for solving constrained optimization problems, Lecture Notes in Artificial Intelligence 4529, Springer-Verlag, Berlin.
Kennedy, J., Eberhart, R. (1995) Particle swarm optimization, In: Proceedings of IEEE International Conference on Neural Networks, Perth, Australia, pp. 1942–1948.
Kennedy, J., Eberhart, R. (1997) A discrete binary version of the particle swarm algorithm, In: Proceedings of IEEE International Conference on Systems, Man, and Cybernetics, Piscataway, NJ, pp. 4104–4109.
Mirjalili S. (2016) ‘SCA: a sine-cosine algorithm for solving optimization problems. Knowledge-Based Systems’, vol. 96, pp. 120–133.
Patel V.K. and Savsani V.J. (2015) ‘Heat transfer search (HTS): a novel optimization algorithm’, Information Sciences, vol. 324, pp. 217–246.
Payne, R. B., Sorenson, M. D., & Klitz, K. (2005). The cuckoos (Vol. 15). Oxford University Press.
Rao SS. (2009) Engineering optimization: theory and practice. John Wiley & Sons.
Rao R.V., Savsani V.J. and Vakharia D.P. (2011) ‘Teaching–learning-based optimization: a novel method for constrained mechanical design optimization problems’, Computer-Aided Design, vol. 43(3), pp. 303–315.
Savsani P. and Savsani V. (2016) ‘Passing vehicle search (PVS): A novel metaheuristic algorithm’, Applied Mathematical Modelling, vol. 40(5–6), pp. 3951–3978.
Storn R., Price K. (1997) ‘Differential evolution – a simple and efficient heuristic for global optimization over continuous spaces’, Journal of Global Optimization, vol. 11, 341–359.
Wolpert, D.H., Macready, W.G. (1997) ‘No free lunch theorems for optimization’, IEEE Transactions on Evolutionary Computation, vol. 1(1), 67–82.
Yang, X. S., & Deb, S. (2009). Cuckoo search via Levey flights. In Proceedings of the World Congress on nature and biologically inspired computing (Vol. 4, pp. 210–214), NABIC: Coimbatore.
Yang, X. S., & Deb, S. (2010). Engineering optimization by cuckoo search. International Journal of Mathematical Modelling & Numerical Optimization, 1(4), 330–343.
Yang, X. S. (2010). Nature-inspired metaheuristic algorithms. Luniver Press.
Zheng Y.J. (2015) ‘Water wave optimization: a new nature-inspired metaheuristic. Computers & Operations Research’, vol. 55, pp. 1–11.
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Patel, V.K., Savsani, V.J., Tawhid, M.A. (2019). Metaheuristic Methods. In: Thermal System Optimization. Springer, Cham. https://doi.org/10.1007/978-3-030-10477-1_2
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DOI: https://doi.org/10.1007/978-3-030-10477-1_2
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