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天然气液化工艺流程的设计优化中所涉及的设备、运行参数以及物流的物性参数众多,加之各热力学方程高度非线性这些特点,国内外一些学者将遗传算法这一优秀算法引入到天然气液化流程的优化设计中。但标准遗传算法在天然气液化工艺的优化设计中容易陷入局部最优的陷阱,且收敛的速度及精度还有待提升。本文根据天然气液化工艺优化设计中待优化参数多,耗时长的特点对标准遗传算法进行改进,改进后的遗传算法在提升全局搜索能力的同时还增强了局部搜索能力,对天然气液化流程的优化设计具有很好的适用性。
Natural gas liquefaction process design and optimization involved in the equipment, operating parameters and physical properties of many logistics parameters, coupled with the highly nonlinear thermodynamic equations of these characteristics, some scholars at home and abroad will genetic algorithm this excellent algorithm is introduced into the optimization of liquefied natural gas process designing. However, the standard genetic algorithm is apt to fall into the trap of local optimum in the optimization design of natural gas liquefaction process, and the speed and accuracy of convergence need to be improved. In this paper, the standard genetic algorithm is improved according to the parameters to be optimized and the time-consuming optimization in the optimal design of natural gas liquefaction process. The improved genetic algorithm also enhances the local search ability while improving the global search ability. The optimized design of natural gas liquefaction process Has good applicability.