Abstract
Abstract In this paper, a new method is presented for optimization of heat exchanger networks making use of genetic algorithm and Sequential Quadratic Programming. The optimization problem is solved in the following two levels: 1- Structure of the optimized network is distinguished through genetic algorithm, and 2- The optimized thermal load of exchangers is determined through Sequential Quadratic Programming. Genetic algorithm uses these values for the determination of the fitness. For assuring the authenticity of the newly presented method, two standard heat exchanger networks are solved numerically. For representing the efficiency and applicability of this method for the industrial issues, an actual industrial optimization problem i.e. Aromatic Unit of Bandar Imam Petrochemistry in Iran is verified. The results indicate that the proposed multistage optimization algorithm of heat exchanger networks is better in all cases than those obtained using traditional optimization methods such as Pinch Analysis Method and Mathematical Optimization Method.
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