## 1 Introduction
So, in the typical building optimization design workflow, building optimization is kind of separated from the design process. An architect proposes a building design first, hands it to engineers or optimization experts to be optimized and then modifies the design based on the optimization results. This process, along with the difficulty in converting between different software models, is a severe limitation for architects to create a design loop in which timely performance feedback can effectively influence overall building forms [29]. Since the application of building multiobjective optimization requires extensive mathematical and computer programming knowledge [30], teaching architectural students and designers the basics of building performance simulation and optimization is necessary and can alleviate this dilemma. From a researcher's perspective, it is necessary to enable architects optimize building design in traditional architectural parametric modeling tools and get timely performance optimization feedback during the building design process. To sum up, the limitations in previous studies can be summarized as follows:  
1. Few studies have explored building many-objective optimization design problems, either through BPS based optimization or ANNs based. The BPS based optimization method can be extremely slow when faced with many-objective problems, while the existing ANN based methods require strong programming skills of coupling multiple algorithms in different software to achieve building many-objective optimization. 2. Most buildings in the case studies were residential or office buildings, and few large-scale public buildings. The foremost reason is that the design of a large-scale public building is highly complex and flexible, and it is very difficult to model the building for performance simulation, the optimization process also takes longer. However, the energy saving potential in per unit area of public buildings is greater, so performance optimization of public buildings is even more necessary. 3. Many studies have used simple hypothetical buildings or oversimplified building models. The hypothetical and simplified modeling methods can reduce the difficulty of building energy simulation modeling and shorten the optimization time, but are very likely to be far from the actual situation. A lack of architectured-friendly software and tools, not to mention an integrated many-objective optimization workflow, which is efficient and architect oriented. In most of the existing studies, optimization process has not been integrated with the building design modeling process. Although in recent years, more and more studies have achieved BPS based multiobjective optimization cases on an architectural parametric modeling platform [14; 15; 16; 17], but the slow feedback of the optimization results still can be a bottleneck. Confronted with the limitations above, this paper aims to propose an architect oriented ANN based many-objective optimization design method to improve the energy, daylighting and cost performance of a large-scale public building. A model fitting the actual building design characteristics was developed for simulation and optimization. In addition, an architect-friendly integrated workflow was implemented based on the architectural parametric modeling platform of a Rhinoceros and Grasshopper.