The Energy Performance of Building Directive (EPBD) obligated all European countries to ensure that nearly-zero-energy codes were the norm for the construction of new buildings while fulfilling the minimum indoor comfort requirements at the national level [
1]. In Sweden, office buildings with a total area of 32.3 million square meters [
2] were responsible for about 6.25 TWh total energy consumption in 2016, which corresponded to the second greatest share among non-residential buildings in the same year [
3]. Accordingly, the construction of office buildings in Sweden has greatly contributed to a reduction in energy demands and greenhouse gases, which also provide economic benefits at the national level [
4].
In addition, former studies show that improving indoor environmental quality, including visual and thermal comfort, contributes to a higher level of productivity and enhanced health [
5,
6], and thereby is conducive to steady economic growth [
7,
8]. A simultaneous decrease in energy demand and costs, while improving the indoor environmental quality, requires constructive communication between building professionals. At this point, Building Information Modelling (BIM) provides a useful platform for sharing information, which streamlines communications and coordinates collaboration between building professionals, including architects, engineers, and energy experts [
9,
10]. Furthermore, the implementation of BIM provides further benefits, as it allows design errors to be discovered more easily and reduces construction times and costs [
10]. The above-mentioned benefits can be complemented by incorporating an optimization algorithm into BIM-based construction projects [
10,
11]. This allows three possibilities: (i) resolving an optimization problem with three objectives at the most, (ii) analyzing the performance of multiple construction solutions with respect to optimization objectives, and (iii) selecting a construction solution based on trade-offs between optimization objectives [
12]. The incorporation can therefore assist building professionals in their decision-making process. For instance, Shadram and Mukkavaara [
13] employed a combination of BIM and an optimization algorithm to find a construction solution based on a trade-off between operational energy and embodied energy for a single detached dwelling in Sweden. Rahmani Asl, Stoupine, Zarrinmehr and Yan [
10] developed a framework based on the incorporation of BIM and an optimization algorithm. They validated the framework by selecting a construction solution based on a trade-off between visual comfort and energy demand for a single detached dwelling in the U.S. Sandberg, Mukkavaara, Shadram and Olofsson [
14] exploited a combination of BIM and an optimization algorithm to select a construction solution based on a trade-off between total energy demand and life-cycle costs for a multifamily residential dwelling in Sweden.
The benefits of incorporation have provided an expeditious enhancement in BIM uptake within the Swedish construction industry [
15] that has led to further investments in adopting BIM in construction projects [
16]. The large construction companies in Sweden make up the greatest share of BIM adopters [
17], while around 58% of the medium sized companies utilized it in construction projects [
18]. One of the main limitations with utilizing BIM is the feasibility of resolving an optimization problem with more than three objectives. This limitation is further illuminated when the construction companies in Sweden are obligated to fulfill the EPBD’s requirements for both reducing energy demand and costs, and to improve visual and thermal comfort. Accordingly, there is a need for a method that allows construction companies to maintain BIM utilization in projects and to exploit its benefits, while overcoming its limitations. Incorporating BIM, an optimization algorithm, and a multi-criteria decision-making (MCDM) method helps to overcome such limitations, thereby allowing the selection of a trade-off construction solution [
19,
20]. A MCDM method considers occupants’ and owners’ preferences and assists them to make an efficient decision [
20]. To the best of the authors’ knowledge, no attempt has been made previously to use BIM, an optimization algorithm, and an MCDM method to select a construction solution based on a trade-off between visual and thermal comfort, energy demands, and life-cycle costs. Accordingly, these methods were exploited to select a trade-off construction solution for an office building in Sweden. Two scenarios were considered when using the incorporation of these methods for selecting a trade-off construction solution. The first scenario emphasized the importance of visual and thermal comfort in the building design process, whereas the second scenario stressed a further decrease in life-cycle costs. The selection of scenarios was based on the current situation in designing office buildings in Sweden, where occupants and owners have mainly different preferences in terms of a building’s performance. Occupants value the indoor environmental quality in office buildings, while owners appreciate lower costs. The outcomes of the two scenarios were later compared to understand how a trade-off construction solution, obtained by prioritizing occupants’ preferences, differed from a trade-off solution achieved following the owners’ preferences.