The Covid-19 pandemic introduces new challenges and constraints for return to work business planning. We describe a space allocation problem that incorporates social distancing constraints while optimising the number of available safe workspaces in a return to work scenario. We propose and demonstrate a graph based approach that solves the optimisation problem via modelling as a bipartite graph of disconnected components over a graph of constraints. We compare results obtained with a constrained random walk and a linear programming approach.

中文翻译：

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社会距离约束下的最优席位分配

Covid-19大流行为重返业务业务规划带来了新的挑战和限制。我们描述了一个空间分配问题，该问题结合了社会疏远约束，同时在返回工作场景中优化了可用安全工作空间的数量。我们提出并演示了一种基于图的方法，该方法通过建模为约束图上的不连续组件的二部图来解决优化问题。我们比较了约束随机游走和线性规划方法获得的结果。