Optimizing Hospital Emergency Department Layout via Multiobjective Tabu Search

Hospital department layout problems (HDLPs) are significant in enhancing service quality and reducing patients' travel distance and time. Their studies are scarce in comparison with those for facility layout problems in manufacturing systems. Existing approaches to HDLPs usually adopt simplified models and thus gain very limited applications in a real world. HDLPs typically involve multiple objectives that may conflict with each other. There have been no studies on their multiobjective heuristic approaches to our best knowledge. In this paper, we propose multiobjective tabu search (MTS) for a real-world HDLP. Beside the frequently used objective of flow cost, ensuring the closeness among certain departments is introduced as another one. A solution coding scheme is designed to represent a solution. A penalty function is devised to handle infeasible solutions. Local search is integrated into tabu search to optimize the assignment of departments. Experiment results show that MTS is able to produce Pareto solutions that outperform those of the comparative method. Compared to the actually implemented layout, solutions produced by MTS can save about 5%-15% patients' travel time (distance).