为了克服换热网络全局最优化过程中极易陷入局部最优解陷阱的难题,本文将蒙特卡罗随机抽样技术应用到换热网络冷、热流体随机组合中,从而实现换热网络多维优化参数优化顺序的随机变化,使得换热网络优化能够从一个局部最小解跳到另外一个局部最小解,实现全局最优化。通过具体算例表明,这种方法能够找到比以往算例更好的结果,能够更好地满足工业上的应用。%In order to overcome the difficulty of being easily trapped in local optimal solution during the global optimization process of heat exchanger network, the Monte-Carlo random sampling technique was applied to the random combination of cold fluid and hot fluid in the heat exchanger network. Through this way, the random changes of optimization sequence about multi-dimensional parameters were accomplished, the global optimal result of heat exchanger network could be sought out during jumping out from one local minimum solution to another. Through a case study, compared with previous results, the better result was obtained using this optimization method which is more suitable to industrial applications.
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