![]() This problem implies an approach that systematically enumerates alternative solutions while considering a broad spectrum of criteria. In particular, in a furniture arrangement problem, a given space must be populated with a set of furniture pieces, resulting in an optimal arrangement according to some design rules. ![]() This study addresses the furniture layout problem, considering IEQ requirements for working environments with multi-occupant office end-use. Conversely, indoor environmental quality concerns diverse sub-domains that affect human life, including visual, thermal and acoustics comfort. 2, several furniture arrangement approaches focus mainly on functional and aesthetic aspects of an indoor layout. However, in the specific problem of furniture layout arrangement, the indoor environmental quality (IEQ) has been either neglected or partially addressed. In particular, recent studies show that desk location and office arrangement significantly impact occupant satisfaction since they are related to the environmental comfort perception (Kwon et al. Improving user satisfaction is beneficial for the employee and the organization, which may increase its financial gains (Seppänen and Fisk 2003). It has been demonstrated that the quality of the working environment improves user satisfaction since it strongly influences occupants’ health, well-being, and productivity (Frontczak and Wargocki 2011 Leaman and Bordass 1999 Colenberg et al. More than 50% of workers in the world spend most of their time in offices (Vimalanathan and Babu 2014). Moreover, numerical results show that the proposed approach can be a valuable tool for evaluating the conformity to the environmental comfort standard of working environments during the furniture layout design phase instead of applying corrections during the post-occupancy evaluation. The experimental results demonstrated that the proposed multi-objective RL approach is able to determine optimal furniture arrangements that provide a balance among office occupants in terms of IEQ satisfaction. We conducted experiments in two different offices. Then, we train the RL agent to produce optimal/suboptimal layout patterns through a Q-learning-based algorithm. Firstly, we formulated the furniture layout task as a MOMDP problem by defining reward functions in terms of thermal, acoustics and visual comfort. ![]() The goal is to determine optimal workstation positions that maximise workers’ IEQ satisfaction and functional aspects of working spaces under analysis. In particular, we explore the furniture arrangement task as a Multi-Objective Markov Decision Process (MOMDP), which is solved by a reinforcement learning (RL) agent. The contribution of this paper is to introduce a novel method for furniture layout optimisation in terms of IEQ requirements in multi-occupant offices. Nevertheless, IEQ has been either neglected or partially addressed in the context of interior design. Specifically, it has been demonstrated that the furniture configuration in working spaces affects the occupant’s comfort perception. In particular, IEQ plays a relevant role in workers’ satisfaction since it strongly influences health, well-being, and productivity. Indoor Environmental Quality (IEQ) concerns several aspects of environmental comforts, such as thermal, visual and acoustics comfort.
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