开发了一种模拟/优化工具来设计建筑外壳，以最大限度地降低与加热和冷却系统相关的能源使用成本。该工具将优化算法与建筑能耗模拟引擎相结合，以选择与住宅建筑围护结构（包括建筑形状）相关的综合参数列表的最佳值。采用了三种优化方法，包括遗传算法（GA）、顺序搜索技术和粒子群技术。本文比较了三种优化方法在不同围护结构参数下的精度和效率。 对于相对较大的搜索空间，研究发现，使用顺序搜索技术所需模拟的60%和粒子群优化方法所需模拟的40%，遗传算法能够以0.4%的精度识别最小代价点。单位:双引文:ASHRAE交易，第115卷，第。2、路易斯维尔2009

A simulation/optimization tool has been developed to design building shell that minimizes energy use costs associated with heating and cooling systems. The tool couples an optimization algorithm to a building energy simulation engine to select optimal values of a comprehensive list of parameters associated with the envelope of residential buildings including the building shape. Three optimization methods are utilized including genetic algorithm (GA) approach, sequential search technique, and particle swarm technique. In this paper, the performance in terms of accuracy and efficiency of the three optimization approaches was compared for various sets of building envelope parameters.For relatively large search spaces, it was found that the GA could identify the minimum cost point to with an accuracy of 0.4% using 60% of the simulations required by sequential search technique and only 40% of the simulations needed by the particle swarm optimization method.Units: Dual