Abstract
Chemical reaction system, dynamic operation can significantly increase the average rate of reaction, improve the time-average selectivity of complex reactions and enhance the molecular weight distribution of certain free-radical polymerization reactions, overcome the thermodynamic limitations of reversible reactions. It even can be used as integrated means of exothermic/endothermic reaction and catalytic reaction/catalyst regeneration, opens up new ways to strengthen and control the reaction process, reduce waste emissions, and increase economic and social benefits. Therefore, it has great significance to model, simulate and calculate the process of chemical reaction. In this paper, a cooperative firefly algorithm is proposed to solve the optimal dynamic model of chemical reaction. The characteristics of the proposed algorithm are analyzed in detailed and the simulation results of the algorithm are given. It provides a feasible solution to solve such problems and the simulation results also show the effectiveness of the proposed algorithm.
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References
Matros, Y.S.: Unsteady-state Processes in Catalytic Reactor. Li Chengyue, Yan Zequn, trans. Science Press, Beijing, October 1994
Huang, Z., Wu, G.: Catalytic reaction processes and mechanism under forced oscillation. Chem. Eng. Prog. (5), 10–15 (1987)
Gong, X.: Computation Method for Optimal Control Problem. Science Press, Beijing (1979)
Zhong, H.: Mathematical Method of Optimal Control and Its Application. Jiangsu Science and Technology Press, Nanjing (1982)
Xiao, J., Zhou, Z.: Application of Ant colony optimization in beer fermentation control. Inf. Control 33(4), 508–512 (2004)
Xu, F., Luo, X.: Mathematical description of dynamic analysis and control design of catalytic cracker regenerator based on dynamic optimization (I) dynamic optimization. J. Chem, Ind. Eng. 60(3), 675–682 (2009)
Yang, X.S.: Nature-inspired Metaheuristic Algorithms. Luniver Press (2008)
Yang, X.-S.: Firefly algorithms for multimodal optimization. In: Watanabe, O., Zeugmann, T. (eds.) SAGA 2009. LNCS, vol. 5792, pp. 169–178. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-04944-6_14
Sayadi, M.K., Ramezanian, R., Ghaffari-Nasab, N.: A discrete firefly meta-heuristic with local search for make span minimization in permutation flow shop scheduling problems. Int. J. Ind. Eng. Comput. 1(1), 1–10 (2010)
Srivatsava, P.R., et al.: Optimal test sequence generation using firefly algorithm. Swarm Evol. Comput. 8, 44–45 (2013)
Horng, M.-H., Liou, R.-J.: Multilevel minimum cross entropy threshold selection based on the firefly algorithm. Expert Syst. Appl. 38, 14805–14811 (2011)
Guo, L., Li, X., Gu, W.: Improved firefly algorithm to solve blocking pipeline scheduling problem. J. Intell. Syst. 8(1), 33–38 (2013)
Roy, J.: Optimization of chemical reactors with respect to flow configuration. J. Optim. Theory Appl. 2(4), 240–259 (1968)
Rajesh, J., Gupta, K., Kusumaker, H.S., Jayaraman, V.K., Kulkarni, B.D.: Dynamic optimization of chemical processes using ant colony framework. Comput. Chem. 25(6), 583–595 (2001)
Zhang, B., Chen, D.: Iterative genetic algorithm and its application in feeding optimization of bioreactors. CIESC J. 56(1), 100–104 (2005)
Peng, X., Geng, R., Du, W., Qian, F.: An improved knowledge evolution algorithm and its application in chemical industry dynamic optimization. J. Chem. Ind. Eng. 63(3), 841–850 (2012)
Liu, Z., Du, W., Pei, R., Qian, F.: Culture algorithm based on knowledge improvement and its application in chemical industry dynamic optimization. CIESC J. 61(11), 2889–2895 (2010)
Acknowledgments
This work is supported by the Project supported by the National Natural Science Foundation of China (Grant No. 21466008, 21566007).
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Mo, Y., Lu, Y., Ma, Y. (2018). Collaborative Firefly Algorithm for Solving Dynamic Control Model of Chemical Reaction Process System. In: Tan, Y., Shi, Y., Tang, Q. (eds) Advances in Swarm Intelligence. ICSI 2018. Lecture Notes in Computer Science(), vol 10941. Springer, Cham. https://doi.org/10.1007/978-3-319-93815-8_42
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DOI: https://doi.org/10.1007/978-3-319-93815-8_42
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