Download Applications of Metaheuristics in Process Engineering by Jayaraman Valadi, Patrick Siarry PDF

By Jayaraman Valadi, Patrick Siarry

Metaheuristics show fascinating houses like simplicity, effortless parallelizability and prepared applicability to types of optimization difficulties similar to genuine parameter optimization, combinatorial optimization and combined integer optimization. they're therefore commencing to play a key position in numerous industrially very important approach engineering functions, between them the synthesis of warmth and mass trade gear, synthesis of distillation columns and static and dynamic optimization of chemical and bioreactors.

This e-book explains state-of-the-art study recommendations in similar computational intelligence domain names and their purposes in real-world strategy engineering. will probably be of curiosity to business practitioners and learn academics.

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Evol. Comput. 6, 182–197 (2002) 55. : Design and retrofit of multiobjective batch plants via a multicriteria genetic algorithm. Comput. Chem. Eng. 27(12), 1723–1740 (2003) 56. : Fragment-based de Novo ligand design by multiobjective evolutionary optimization. J. Chem. Inf. Model. 48(3), 679–690 (2008) 57. : Multiobjective optimization for multiproduct batch plant design under economic and environmental considerations. Comput. Chem. Eng. 30(4), 599–613 (2006) 58. : Synthesis of heat exchanger networks using genetic algorithms.

Controller are computed at each time step using GA. This technique provided the design of predictive controller with significant improvement over existing predictive control techniques. Doma et al. [61] presented a methodology for the process operating under multivariable control for identifying multiple-input multiple-output step response model using GA with application to a distillation tower in a petroleum refinery. Grosman and Lewin [94] proposed the application of GP to empirical process modeling and for a nonlinear model predictive control.

Rahimpour and Behjati [189] applied GA for the generation of optimal temperature control profile along the membrane dual-type methanol reactor in the presence of catalyst deactivation. Egea et al. [69] proposed an enhanced SS method for the global dynamic optimization of nonlinear processes using the control vector parameterization approach. Lu et al. [149] proposed a combination of PSO and robust eigenvalue assignment method for the process design under uncertainty. Zhang et al. [268] proposed DE algorithm to solve the parameter estimation problems for modeling vapor–liquid equilibrium data.

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