Imperial College London
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ProfessorJenniferWhyte

Faculty of Engineering, Department of Civil and Environmental Engineering

Laing O'Rourke/RAEng Chair in Systems Integration
 
 
 
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Contact

 

+44 (0)20 7594 9245j.whyte Website

 
 
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Assistant

 

Mr Tim Gordon +44 (0)20 7594 5031

 
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Location

 

436Skempton BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Shi:2020:10.1016/j.autcon.2020.103187,
author = {Shi, F and K, Soman R and Han, J and Whyte, J},
doi = {10.1016/j.autcon.2020.103187},
journal = {Automation in Construction},
title = {Addressing adjacency constraints in rectangular floor plans using Monte-Carlo Tree Search},
url = {http://dx.doi.org/10.1016/j.autcon.2020.103187},
volume = {115},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Manually laying out the floor plan for buildings with highly-dense adjacency constraints at the early design stage is a labour-intensive problem. In recent decades, computer-based conventional search algorithms and evolutionary methods have been successfully developed to automatically generate various types of floor plans. However, there is relatively limited work focusing on problems with highly-dense adjacency constraints common in large scale floor plans such as hospitals and schools. This paper proposes an algorithm to generate the early-stage design of floor plans with highly-dense adjacency and non-adjacency constraints using reinforcement learning based on off-policy Monte-Carlo Tree Search. The results show the advantages of the proposed algorithm for the targeted problem of highly-dense adjacency constrained floor plan generation, which is more time-efficient, more lightweight to implement, and having a larger capacity than other approaches such as Evolution strategy and traditional on-policy search.
AU  - Shi,F
AU  - K,Soman R
AU  - Han,J
AU  - Whyte,J
DO  - 10.1016/j.autcon.2020.103187
PY  - 2020///
SN  - 0926-5805
TI  - Addressing adjacency constraints in rectangular floor plans using Monte-Carlo Tree Search
T2  - Automation in Construction
UR  - http://dx.doi.org/10.1016/j.autcon.2020.103187
UR  - http://hdl.handle.net/10044/1/78969
VL  - 115
ER  -
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