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DESCRIPTION:Sentao Miao\n\nLeeds School of Business\, University of Colorad
 o\n\nData-Driven Facility Layout for Enhancing Walk Appeal in Walkable Nei
 ghborhoods\n\nDate: Friday\, May 1\, 2026\n	Time: 11:00 AM - 12:00 PM\n	Loca
 tion: Armstrong Room 375\n\n\nAbstract\n\nIn response to the challenges po
 sed by car-centric urban development\, there is growing global advocacy fo
 r walkable neighborhoods that promote public health and urban sustainabili
 ty. To support the design of such neighborhoods\, this paper studies the o
 ptimal layout of facilities (e.g.\, retail and service establishments) to 
 enhance walk appeal. Unlike conventional designs that rely primarily on di
 stance metrics\, our approach focuses on pedestrian choices. We use a late
 nt class logit model to estimate how facility layouts influence individual
 s’ propensity to walk\, accounting for heterogeneous travel purposes. This
  model is calibrated with a city-wide dataset from our industry collaborat
 or\, a leading Chinese map service provider. Building on this model\, we d
 evelop a choice-based optimization framework to determine facility layouts
  that maximize the aggregate walking probability of residents. We first an
 alyze its structural properties to derive analytical insights into optimal
  layout patterns. To find optimal layouts for this NP-hard problem\, we re
 formulate it as an exponential cone program. To address the computational 
 challenges this poses for large-scale applications\, we further develop ef
 ficient greedy algorithms and establish their performance guarantees via s
 ubmodularity ratio analysis. A case study in Beijing shows that our approa
 ch significantly improves walk appeal compared to traditional methods\, wi
 th minimal impact on facility accessibility. Our results also reveal a “wi
 sdom of crowds” effect in existing layouts and emphasize the importance of
  neighborhood context in shaping optimal design patterns. Specifically\, w
 e find that dispersed layouts are preferable in already walkable environme
 nts\, while more challenging walking conditions benefit from spatially con
 centrated facilities.\n
DTSTART:20260501T150000Z
DTEND:20260501T160000Z
LOCATION:Room 375\, Donald E. Armstrong Building\, CA\, QC\, Montreal\, H3A
  3L1\, 3420 rue McTavish
SUMMARY:Management Science Research Centre (MSRC) Seminar: Sentao Miao
URL:/dobson/channels/event/management-science-research
 -centre-msrc-seminar-sentao-miao-372739
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