Lifting demand-based zoning for minimizing worker vertical transportation time in high-rise building construction

Abstract With an increase in the number of high-rise building construction projects over the last decade, efficient vertical transportation of resources during construction has become increasingly important. Zoning divides the lifting demand into several vertical clusters of floors and assigns a group of lifts for each cluster. Although zoning has great potential in minimizing the vertical transportation time, it is challenging to derive an optimal zoning configuration for the construction of high-rise buildings because lifting demand can vary significantly with construction progress. To address this challenge, this paper introduces a simulation model that can assist in determining the optimal zoning configuration under varying lifting demand. Application of the model to a high-rise residential building project shows that lifting demand-based zoning can reduce the vertical transportation time by about 40%. Based on this, it is concluded that the model has a great potential to minimize workers' idle time and increase labor productivity. This paper is of relevance to researchers with respect to the development of a mathematical model that can identify the optimal zoning configuration. This paper is also of value to practitioners in terms of providing an effective tool to optimize the vertical transportation plan in the construction of a high-rise building.

[1]  Matthew Brand,et al.  Optimal parking in group elevator control , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[2]  R. H. Myers,et al.  STAT 319 : Probability & Statistics for Engineers & Scientists Term 152 ( 1 ) Final Exam Wednesday 11 / 05 / 2016 8 : 00 – 10 : 30 AM , 2016 .

[3]  Suying Yang,et al.  Dynamic Partition of Elevator Group Control System with Destination Floor Guidance in Up-peak Traffic , 2009, J. Comput..

[4]  Yoonseok Shin,et al.  Simulation model incorporating genetic algorithms for optimal temporary hoist planning in high-rise building construction , 2011 .

[5]  Seokyon Hwang Planning Temporary Hoists for Building Construction , 2009 .

[6]  Thomas Strang,et al.  Context-Aware Elevator Scheduling , 2007, 21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07).

[7]  Chi Ming Tam,et al.  Optimization of material hoisting operations and storage locations in multi-storey building construction by mixed-integer programming , 2010 .

[8]  A Tp So,et al.  Intelligent supervisory control for lifts: dynamic zoning , 2001 .

[9]  Lutfi Al-Sharif,et al.  Elevator Traffic Handbook: Theory and Practice , 2003 .

[10]  Soon-Wook Kwon,et al.  SIMULATION METHOD OF CONSTRUCTION HOIST OPERATING PLAN FOR HIGH RISE BUILDINGS CONSIDERING LIFTING HEIGHTS AND LOADS , 2010 .

[11]  G. W. Snedecor Statistical Methods , 1964 .

[12]  Photios G. Ioannou,et al.  Scalable simulation models for construction operations , 1996, Winter Simulation Conference.

[13]  Pablo Cortés,et al.  Genetic algorithm for controllers in elevator groups: analysis and simulation during lunchpeak traffic , 2004, Appl. Soft Comput..

[14]  Gordon F. Newell,et al.  STRATEGIES FOR SERVING PEAK ELEVATOR TRAFFIC , 1998 .