HVAC optimisation studies: Sizing by genetic algorithm
HVAC optimisation studies: Sizing by genetic algorithm
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DOI：
10.1177/014362449601700102
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发表时间：
1996-02
影响因子：
1.7
通讯作者：
Jonathan A. Wright
中科院分区：
文献类型：
--
作者：
Jonathan A. Wright
以前对暖通空调系统最优规模的研究主要集中在直接搜索优化方法的使用上。虽然这些方法可以找到解，但它们很难沿着非线性约束边界移动离散变量，结果往往是失败的。本文描述了一种简单的遗传算法搜索方法在解决这类问题时的性能。文中描述了问题的形式和算法的运算过程。结果表明，该算法具有较快的初始收敛速度，但由于优化问题的高度约束性，最终收敛较慢。结果表明，更有效地利用约束函数可以提高算法的收敛速度和鲁棒性。算法的性能对问题的表述也很敏感。
Previous research into the optimum sizing of hvac systems has focused on the use of direct search optimisation methods. Although these methods can find a solution, it is difficult for them to move discrete variables along nonlinear constraint boundaries and they often fail as a result. This paper describes the performance of a simple genetic algorithm search method when applied to such a problem. The formulation of the problem is described together with the operation of the algorithm. It is concluded that the algorithm exhibits rapid initial progress but that final convergence is slow due to the highly constrained nature of the optimisation problem. It is suggested that a more effective use of the constraint functions could improve the convergence and robustness of the algorithm. The performance of the algorithm is also sensitive to the problem formulation.