1 Srinivasan, B., Palanki, S., Bonvin, D., “Dynamic optimization of batch processes I: Characterization of the nominal solution”, Compu. Chem. Eng., 27, 1-26 (2003).2 Irizarry, R., “A generalized framework for solving dynamic optimization problems using the artificial chemical process paradigm: Applications to particulate processes and discrete dynamic systems”, Chem. Eng. Sci., 60, 5663-5681 (2005).3 Zhang, B., Yu, H.J., Chen, D.Z., “Sequential optimization of chemical dynamic problems by ant-colony algorithm”, J. Chem. Eng. Chin. Univ., 20 (1), 120-125 (2006). (in Chinese)4 Biegler, L.T., Cervantes, A.M., Wachter, A., “Advances in simultaneous strategies for dynamic process optimization”, Chem. Eng. Sci., 57, 575-593 (2002).5 Eva, B.C., Vassilios, S.V., Julio, R. B., “Dynamic optimization of single- and multi-stage systems using a hybrid stochastic-deterministic method”, Ind. Eng. Chem. Res., 44, 1514-1523 (2005).6 Julio, R. B., Eva, B.C., Carmen, G.M., Antonio, A.A., “Dynamic optimization of bioprocesses: Efficient and robust numerical strategies”, J. Biotechnol., 117, 407-419 (2005).7 Faber, R., Jockenhovel, T., Tsatsaronis, G., “Dynamic optimization with simulated annealing”, Compu. Chem. Eng., 29, 273-290 (2005).8 Mekarapiruk, W., Luus, R., “Optimal control by iterative dynamic programming with deterministic and random candidates for control”, Ind. Eng. Chem. Res., 39, 84-91 (2000).9 Hong, W.R., Tan, P.C., Wang, S.A.Q., Pu, L., “A comparison of arithmetic operations for dynamic process optimization approach”, Chin. J. Chem. Eng., 18 (1), 80-85 (2010).10 Tebbani, S., Dumur, D., Hafidi, G., “Open-loop optimization and trajectory tracking of a fed-batch bioreactor”, Chem. Eng. Proce., 47, 1933-1941 (2008).11 Jose, A.E., Eva, B.C., Garcia, M.S., Julio, R.B., “Dynamic optimization of nonlinear processes with an enhanced scatter search method”, Ind. Eng. Chem. Res., 48, 4388-4401 (2009).12 He, Y.J., Yu, H.J., Cheng, B., Chen, D.Z., “Multi-objective particle swarm optimization approach to solution of fed-batch bioreactor dynamic multi-objective optimization”, J. Chem. Ind. Eng., 58 (5), 1262-1270 (2007). (in Chinese)13 Rajesh, J., Gupta1, K., Kusumakar, H.S., Jayaraman, V.K., Kulkarni, B.D., “Dynamic optimization of chemical processes using ant colony framework”, Compu. Chem., 25, 583-595 (2001).14 Sarkar, D., Modak, J.M., “Optimisation of fed-batch bioreactors using genetic algorithms”, Chem. Eng. Sci., 58, 2283-2296 (2003).15 Zhang, B., Chen, D.Z., “Iterative genetic algorithm and its application to policies optimization for bioreactor”, J. Chem. Ind. Eng., 56 (1), 100-104 (2005). (in Chinese)16 He, Y.J., Chen, D.Z., “Immune mechanism based multi-objective ant colony algorithm approach to batch reactor constrained dynamic multi-objective optimization problems”, J. Chem. Eng. Chin. Univ., 23 (2), 326-332 (2009). (in Chinese)17 Zhang, B., Chen, D.Z., Zhao, W.X., “Iterative ant-colony algorithm and its application to dynamic optimization of chemical process”, Compu. Chem. Eng., 29, 2078-2086 (2005).18 Tfaili, W., Siarry, P., “A new charged ant colony algorithm for continuous dynamic optimization”, Appl. Math. Compu., 197, 604-613 (2008).19 Asgari, S.A., Mahmoud, R.P., “Dynamic optimization in chemical processes using region reduction strategy and control vector parameterization with an ant colony optimization algorithm”, Chem. Eng. Technol., 31 (4), 507-512 (2008).20 Shelokar, P.S., Jayaraman, V.K., Kulkarni, B.D., “Multicanonical jump walk annealing assisted by tabu for dynamic optimization of chemical engineering processes”, Eur. J. Ope. Res., 185, 1213-1229 (2008).21 Jorge, E.J., Ines, M.S., Isidoro, G.G., “Optimization of biotechnological processes. The acetic acid fermentation. Part III: Dynamic optimization”, Biochem. Eng. J., 45, 22-29 (2009).22 Kasprzyk, G.P., Jasku, M., “Application of the hybrid genetic-simplex algorithm for deconvolution of electrochemical responses in SDLSV method”, J. Electra. Chem., 567, 39-66 (2004).23 Fan, S.K., Zahara, E., “A hybrid simplex search and particle swarm optimization for unconstrained optimization”, Eur. J. Ope. Res., 181, 527-548 (2007).24 Ren, Z.W., San, Y., Chen, J.F., “Hybrid simplex-improved genetic algorithm for global numerical optimization”, Acta Automatica Sinica, 33, 91-95 (2007).25 Zahara, E., Kao, Y.T., “Hybrid Nelder-Mead simplex search and particle swarm optimization for constrained engineering design problems”, Exp. Sys. Appl., 36, 3880-3886 (2009).26 Amel, K., Mohamed, J., Moncef, C., “The use of the simplex method and its derivatives to the on-line optimization of the parameters of an injection molding process”, Chem. Intell. Lab. Sys., 96, 117-122 (2009)27 Gong, X.F., Computation Method for Optimal Control Problem, Science Press, Beijing (1979). (in Chinese)28 Park, S., Ramirez, W.F., “Optimal production of secreted protein in fed-batch reactors”, AIChE J., 34 (8), 1550-1558 (1988).29 Tholudur, A., Ramirez, W.F., “Obtaining smoother singular arc policies using a modified iterative dynamic programming algorithm”, Inter. J. Control., 8 (5), 1115-1128 (1997).30 Balsa-Canto, E., Banga, J.R., “Efficient optimal control of bioprocesses using second-order information”, Ind. Eng. Chem. Res., 39 (11), 4287-4295 (2000).31 Balso-Canto, E., Banga, J.R., Alonso, A.A., Vassiliadis, V.S., “Dynamic optimization of chemical and biochemical processes using restricted second-order information”, Compu. Chem. Eng., 25, 539-546 (2001).32 Sarkar, D., Modak, J.M., “ANNSA: A hybrid artificial neural network/simulated annealing algorithm for optimal control problems”, Chem. Eng. Sci., 58, 3131-3142 (2003).33 Mo, Y.B., Chen, D.Z., Hu, S.X., “Chaos particle swarm optimization algorithm and its application in biochemical process dynamic optimization”, J. Chem. Ind. Eng., 57 (9), 2123-2127 (2006). (in Chinese) |