Abstract
Building renovation is an effective way to revive the use of a building, the use efficiency of which is primarily determined by its layout. However, in architectural practice, architects and building owners renovate buildings based on their personal subjective perceptions of how occupants use the building instead of systematically analyzing their use behaviors. This study proposes a model, called the Function-space Assignment and MOvement Simulation (FAMOS) model, which integrates radio frequency identification (RFID), fast messy genetic algorithms (fmGA), and movement simulation techniques to solve the function-space assignment problem. The RFID equipment is specifically used to track the occupants’ movement data in a building, the fmGA is employed to identify the optimal result of function assignment, and the movement simulation technique is adopted to verify the result and support the decision-making of function-space assignment. This study presents a real case study to demonstrate the use of FAMOS and compare its assignments with those generated by a renovation architect. The objective function showed that FAMOS’s version had a 14.80% higher objective value than the architect’s version. The experiment also showed that FAMOS helped the architect find the best assignment or improve their assignment based on desired objectives such as preferred space size, minimized movement distance, or removal of corridor congestion.
Highlights
Assigning appropriate functions to building spaces is one of the most important factors in determining the use performance of an existing building
This study proposes a model, called the Function-space Assignment and MOvement Simulation (FAMOS) model, which attempts to optimize the function assignment by sensing occupant movement data, data-mining the function-space relationship, finding optimized function-space assignment using fast messy genetic algorithms (fmGA), and verifying its achievement on the objective function and other objectives not included in the function using simulation
This study presents the FAMOS model, which takes occupants’ movement data and building floor plans as its input, and searches for the optimal function-space assignment in a building
Summary
Assigning appropriate functions to building spaces is one of the most important factors in determining the use performance of an existing building. Instead of relying on the trial and error attempts of the facility administrator to find the optimum layout, mathematical optimization algorithms can be used to design the layout of hospitals, factory assembly lines, and construction sites once quantifiable data on the occupants’ movements are available Another prevailing problem is that the administrator may lack the means to quantitatively verify their proposed function-assignment to assess its performance. Instead of relying on subjective experience or opinions, a researcher can monitor the activities of building occupants manually or by using location-tracking technologies to collect quantitative data on occupants’ movement These technologies include WiFi-based systems, infrared systems, ultrasound, scene analysis, and RFID (Tesoriero et al 2010). This study proposes a model, called the Function-space Assignment and MOvement Simulation (FAMOS) model, which attempts to optimize the function assignment by sensing occupant movement data, data-mining the function-space relationship, finding optimized function-space assignment using fmGA, and verifying its achievement on the objective function and other objectives not included in the function using simulation
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