CONSTRAINED MULTIOBJECTIVE OPTIMIZATION OF A CONDENSER COIL USING EVOLUTIONARY ALGORITHMS

摘要

Air cooled cross-flow heat exchangers are an integral part of refrigeration and air-conditioning systems. The design and selection of a particular heat exchanger depends on its performance and the associated economic parameters, which in turn depend on individual components that make up the heat exchanger. A multiobjective genetic algorithm is applied to the optimization of an air cooled condensing unit. The primary optimization objectives are the performance of the condenser coil and the cost. This study illustrates how genetic optimization algorithms can be a powerful tool to develop optimal designs for air cooled condensers. At the end of the optimization run, the decision maker is presented with a set of Pareto optimal solutions from which the decision maker can choose appropriate solutions. Optimization setup and results are discussed and conclusions drawn.