摘要
Inspired by genetic algorithm(GA),an improved genetic algorithm(IGA)is proposed.It inherits the main idea of evolutionary computing,avoids the process of coding and decoding inorder to probe the solution in the state space directly and has distributed computing version.Soit is faster and gives higher precision.Aided by IGA,a new optimization strategy for theflexibility analysis and retrofitting of existing heat exchanger networks is presented.A case studyshows that IGA has the ability of finding the global optimum with higher speed and better preci-sion.
Inspired by genetic algorithm(GA), an improved genetic algorithm(IGA) is proposed. It inherits the main idea of evolutionary computing, avoids the process of coding and decoding in order to probe the solution in the state space directly and has distributed computing version. So it is faster and gives higher precision. Aided by IGA, a new optimization strategy for the flexibility analysis and retrofitting of existing heat exchanger networks is presented. A case study shows that IGA has the ability of finding the global optimum with higher speed and better precision.
