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). Note to Practitioners - Layout design of hospital departments is significant in enhancing service quality and reducing patients' travel distance. A real-world department layout problem is difficult to solve since many factors need to be considered and multiple optimization objectives must be sought. This paper presents a multiobjective tabu search approach for such a problem with both objectives to minimize patients' flow cost and departments' closeness. This approach is able to provide multiple Pareto solutions (layouts) for decision makers to choose based on their preferences. Layouts created by this approach can significantly reduce patients' travel time (distance) while satisfying the closeness requirement of departments.