The Improvement Research Of Differential Evolution Method Applied In Heat Exchanger Network Synthesis

Heat exchanger network synthesis(HENS)has a domain role in realizing energy recovery and utilization,and its reasonable design,high efficiency is directly related to the production cost of the whole industrial system.The optimization methods of heat exchanger networks are numerous,mainly included pinch method,deterministic method and heuristic method,the pinch method cannot obtain optimal network structure,the traditional optimization method based on gradient also be difficult to apply to the seriously nonconvex and nonlinear heat exchanger network optimization.Differential evolution(DE)algorithm is applied in heat exchange network optimization,and based on parameter analysis,this paper introduced the dynamic enhanced local search strategy of differential evolution algorithm to optimize heat exchanger network,the opposite population of initial population was repeatedly used to improve the diversity of the population.The main research content is as follows:Firstly,the paper is based on Grossmann's stage-wiser super structure model of heat exchanger networks;we can find the performance of the algorithm depends heavily on the choice of control parameters by use of parameter analysis.We analyzed the effects of parameter on the optimal performance by orthogonal experiment to provide certain reference value about parameter settings.Furthermore,mechanism analysis of premature convergence for differential evolution algorithm was presented,and the algorithm easily gets trapped in local optimum for large heat exchanger networks.A real time factor was set up to keep the value change gradually with the increase of evolution algebra in the iteration process to solve this,the local search ability around the optimum was improved.And on this basis an improvement strategy of differential evolution algorithm was presented,considering dynamic local search strategy combined with forced out of the mechanism to avoid the problem of weak ability and premature convergence.The results show the improvement model is available to heat exchanger network synthesis,the precision and convergence rate of the differential evolution algorithm was increased.Afterwards,the opposite population is built by using the initial population,keeping the original population and the opposite population parallel evolution,an opposite multi-population differential evolution algorithm is proposed to increase the diversity of population.Classic cases were used to prove that the opposition population individuals can acquire more opportunities of “mutation”,and enhance the global optimization ability of the algorithm.Many examples were calculated to show that we can get a better solution.A cooperative mutation operator and a hybrid search algorithm based on multi-population was built to accelerate information exchange between populations,optimal performance of the algorithm was improved,attention must be paid to local search ability as well as global search capability.By several cases,the method can effectively balance the global search and local optimization ability of the algorithm...