@inproceedings{363094db716442afa8ff5c3cf7c90806,
title = "Evaluating Generated Layouts in a Healthcare Departmental Adjacency Optimization Problem",
abstract = "The effective layout of departments within a new hospital influences the efficiency and effectiveness of delivering healthcare services. This study explores a computational approach to generate and evaluate potential hospital layouts. Given a set of healthcare departments, areas, and structural bay sizes, a graph theoretical approach with a placement strategy was used to develop an initial set of optimal and near optimal layouts based on both adjacency ratings and distances. Input data of adjacency ratings was collected from experts involved in the design of a new hospital project. An optimal adjacency graph was calculated and a placement strategy with a discrete set of constraints was used. Each layout was given a distance weighted score based on the pair-wise distance weighted adjacency rating. Healthcare planning and design experts were surveyed for their input on the use of this approach. Comparison of their results to the layout scores indicate that planning and design experts select the best scoring layouts more consistently than the worst scoring layouts.",
author = "Lather, {Jennifer I.} and Timothy Logan and Kate Renner and Messner, {John I.}",
note = "Publisher Copyright: {\textcopyright} 2019 American Society of Civil Engineers.; ASCE International Conference on Computing in Civil Engineering 2019: Data, Sensing, and Analytics, i3CE 2019 ; Conference date: 17-06-2019 Through 19-06-2019",
year = "2019",
language = "English (US)",
series = "Computing in Civil Engineering 2019: Data, Sensing, and Analytics - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019",
publisher = "American Society of Civil Engineers (ASCE)",
pages = "539--546",
editor = "Cho, {Yong K.} and Fernanda Leite and Amir Behzadan and Chao Wang",
booktitle = "Computing in Civil Engineering 2019",
address = "United States",
}