Yongqi Zhang
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Joint Computational Design of Workspaces and Workplans

Yongqi Zhang, Haikun Huang, Erion Plaku, Lap-Fai Yu

George Mason University


Humans assume different production roles in a workspace. On one hand, humans design workplans to complete tasks as efficiently as possible in order to improve productivity. On the other hand, a nice workspace is essential to facilitate teamwork. In this way, workspace design and workplan design complement each other. Inspired by such observations, we propose an automatic approach to jointly design a workspace and a workplan. Taking staff properties, a space, and work equipment as input, our approach jointly optimizes a workspace and a workplan, considering performance factors such as time efficiency and congestion avoidance, as well as workload factors such as walk effort, turn effort, and workload balances. To enable exploration of design trade-offs, our approach generates a set of Pareto-optimal design solutions with strengths on different objectives, which can be adopted for different work scenarios. We apply our approach to synthesize workspaces and workplans for different workplaces such as a fast food kitchen and a supermarket. We also extend our approach to incorporate other common work considerations such as dynamic work demands and accommodating staff members with different physical capabilities. Evaluation experiments with simulations validate the efficacy of our approach for synthesizing effective workspaces and workplans.

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@article{workspace, author = {Yongqi Zhang and Haikun Huang and Erion Plaku and Lap-Fai Yu}, title = {Joint Computational Design of Workspaces and Workplans}, journal = {ACM Transactions on Graphics}, volume = {40}, number = {6}, year = {2021}}


We are grateful to the anonymous reviewers for their constructive comments. This research is supported by an NSF Graduate Research Fellowship and an NSF CAREER Award (award number: 1942531). The work by E. Plaku is supported by (while serving at) the National Science Foundation. Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.