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An Activity‐Based Simulation Model for Assessing Function Space Assignment for Buildings: A Service Performance Perspective
Author(s) -
Dzeng RenJye,
Wang WeiChih,
Hsiao FanYi,
Xie YanQing
Publication year - 2015
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/mice.12177
Subject(s) - function (biology) , computer science , space (punctuation) , process (computing) , service (business) , perspective (graphical) , noise (video) , simulation , operations research , engineering , artificial intelligence , economy , evolutionary biology , economics , biology , operating system , image (mathematics)
Function space assignment determines the function of all spaces and is essential to the design of a remodeled building. Optimization of function space assignment that relies upon users' activities is difficult due to the lack of quantifiable and detailed data about users' activities. In this paper, an activity‐based simulation process model consisting of five phases is proposed and applied to an actual project. The phases include activity data collection, activity simulation, space movement pattern mining, function‐space assignment optimization, movement simulation and assessment. The process also allows the building administrator to adjust the optimized assignment to accommodate hard‐to‐quantify preferences via a variety of indexes such as movement distance, corridor flow, and other space usage‐related indexes. Results from application of the proposed model to an actual remodeling project indicated that the model offered the administrator a better assignment than the contracted architect, with a 5.79% increase in the objective function and a 23.92% decrease in movement distance. The adjusted assignment based on service‐related indices, such as noise interference, further improved service by accounting for parameters that were not easily included in the objective function for optimization.