Global optimization
Evolutionary and Adaptive Computing in Engineering Design: The Integration of Adaptive Search Exploration and Optimization with Engineering Design Pro
On search for optimal control in a problem of bio technology
CompSysTech '07 Proceedings of the 2007 international conference on Computer systems and technologies
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Optimal process design often requires the solution of mixed integer non-linear programming problems. Optimization procedures must be robust and efficient if they are to be incorporated in automated design systems. For heat integrated separation process design, a natural hybrid evolutionary/local search method with these properties is possible. The method is based on the use of local search methods for the continuous design parameters for the units in the process and the use of an evolutionary optimization procedure for the design of the heat exchanger network. The use of a stochastic method for the heat exchanger network aspect introduces noise in the evaluation of the objective function used by the local search methods. A smoothing procedure has been designed and implemented to improve the efficacy of the hybrid approach.This paper presents the evaluation of a variety of local search methods. It is shown that the Hooke and Jeeves algorithm, combined with a simple genetic algorithm, provides a robust, efficient and effective solution procedure for optimizing heat integrated distillation sequences.