Application progress of stochastic searching techniques in the optimization of heat exchanger networks

With the increasing requirement on energy utilization,synthesis and optimization of heat exchanger network have been obtained great interests.The recent developments of the application of random search algorithms in heat exchanger network optimization are reviewed in this paper.Four main stochastic searching techniques including genetic algorithm,simulated annealing algorithm,particle swarm algorithm,and tabu search algorithm are introduced,and the strength and weakness of these algorithms are further discussed,respectively.And a promising research direction to solve a large scale heat-exchanger network optimization problem by using a hybrid algorithm is presented.