基于多重群体遗传算法的换热网络同步综合

通过对YEE换热网络分级超结构的分析和改进,建立了包含更多可行结构的换热网络超结构及其数学模型,扩大了网络结构的搜索范围。针对普通遗传算法和其他优化算法无法保证换热网络综合质量和效率的缺点,结合多重群体遗传算法进行网络优化综合,提高优化过程的稳定性,该方法将换热网络结构信息转化为种群和繁殖群体中个体的染色体信息,选择繁殖种群中优秀个体进入种群淘汰较差个体,实现种群的逐步新陈代谢。利用多重群体遗传算法对实际换热网络问题进行了优化。结果表明:多重群体遗传算法能有效提高换热网络优化的稳定性和鲁棒性,在优化变量和非凸性增加时,能获得综合性能良好的换热网络结构。

Heat exchanger network synthesis with multi-group genetic algorithm

Heat exchanger network superstructure and mathematic model with more practical structure were set up based on analysis and improvement of YEE′s superstructure.Structure searching area was extended.To overcome the shortcoming of optimization property and efficiency of normal genetic algorithm and other methods,multi-group genetic algorithm was used to enhance the stability in the synthesis process.Structure was transformed into individual chromosome information in the population and reproduction population,outstanding individual entered the population to eliminate the bad individual,gradually metabolism of the population was realized.A practical heat exchanger network synthesis problem was solved with multi-group genetic algorithm.The result shows that stability and robust are improved using multi-group genetic algorithm.Heat exchanger network with favorable overall performance can be obtained using this method while optimized variable and non-convexity are increased.