With the advancement in and integration of building energy simulation and optimization tools, building design optimization considering different design objectives and involving multiple disciplines has become technically feasible. However, this multifaceted approach unavoidably increases the dimension of the problem and comes with a prohibitively high computational cost. Hierarchical decomposition divides an optimization problem into several interconnected subproblems, and each subproblem has its objectives and constraints. Therefore, a complex problem is represented by a series of manageable subproblems. However, solving subproblems may lead to the local optimal solutions of the original problem. This research proposes a hierarchical decomposition approach that can achieve global optimal solutions. The proposed approach is applied to a multi-objective optimization problem to minimize the carbon emission and operating cost of building. This problem is decomposed into two subproblems to be solved sequentially. The first subproblem is to minimize the energy consumptions of the building. The second subproblem has the same objectives as the original one, but the search space is the result of the first subproblem. The benefit of decomposing this problem is that only the second problem needs to be solved again when additional energy price and carbon emission scenarios to be considered. A mid-rise residential building is selected as a case study to demonstrate the approach. The results show that the decomposition approach can reduce the number of simulations while keeping the full set of solutions of the original problem. The application of the proposed approach is based on a fixed utility rate, and only two objectives are considered for each level of optimization. These limitations could be overcome by adjusting the way to apply this approach.

随着建筑能耗模拟和优化工具的进步和集成，考虑不同设计目标、​​涉及多学科的建筑设计优化在技术上已经变得可行。然而，这种多方面的方法不可避免地增加了问题的维度，并带来了高得令人望而却步的计算成本。层次分解将一个优化问题分解为几个相互关联的子问题，每个子问题都有其目标和约束。因此，一个复杂的问题由一系列可管理的子问题表示。然而，解决子问题可能会导致原始问题的局部最优解。本研究提出了一种可以实现全局最优解的分层分解方法。所提出的方法应用于多目标优化问题，以最小化建筑的碳排放和运营成本。这个问题分解成两个子问题依次解决。第一个子问题是最小化建筑物的能源消耗。第二个子问题的目标与原问题相同，但搜索空间是第一个子问题的结果。分解这个问题的好处是，当考虑额外的能源价格和碳排放情景时，只需要再次解决第二个问题。选择一栋中层住宅建筑作为案例研究来演示该方法。结果表明，分解方法可以减少模拟次数，同时保留原始问题的全套解决方案。所提出方法的应用基于固定的效用率，每个优化级别只考虑两个目标。这些限制可以通过调整应用这种方法的方式来克服。