Abstract
Simulation is a powerful tool for planning and scheduling highly repetitive tasks in a construction project. However, sensitivity analysis has to be utilized to find the best resource combination to execute the construction tasks. By performing the sensitivity analysis, various resource combinations can be evaluated in terms of their effects on the operation's production and cost. The results of the sensitivity analysis can assist project managers in planning effective resource assignments based on their goals, such as maximizing the system's production rate or minimizing the system's unit cost. However, it is time-consuming to conduct the sensitivity analysis if there are a large number of resource alternatives available. This paper proposes a hybrid mechanism that integrates heuristic algorithms and genetic algorithms to efficiently locate the best resource combination for the construction simulation optimization. Results show that this new hybrid mechanism not only locates the optimal solution but also reduces tremendous computational efforts.
| Original language | English |
|---|---|
| Pages (from-to) | 85-98 |
| Number of pages | 14 |
| Journal | Automation in construction |
| Volume | 14 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2005 Jan 1 |
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All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Civil and Structural Engineering
- Building and Construction
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A hybrid mechanism for optimizing construction simulation models. / Cheng, Tao Ming; Feng, Chung-Wei; Chen, Yan Liang.
In: Automation in construction, Vol. 14, No. 1, 01.01.2005, p. 85-98.Research output: Contribution to journal › Article
TY - JOUR
T1 - A hybrid mechanism for optimizing construction simulation models
AU - Cheng, Tao Ming
AU - Feng, Chung-Wei
AU - Chen, Yan Liang
PY - 2005/1/1
Y1 - 2005/1/1
N2 - Simulation is a powerful tool for planning and scheduling highly repetitive tasks in a construction project. However, sensitivity analysis has to be utilized to find the best resource combination to execute the construction tasks. By performing the sensitivity analysis, various resource combinations can be evaluated in terms of their effects on the operation's production and cost. The results of the sensitivity analysis can assist project managers in planning effective resource assignments based on their goals, such as maximizing the system's production rate or minimizing the system's unit cost. However, it is time-consuming to conduct the sensitivity analysis if there are a large number of resource alternatives available. This paper proposes a hybrid mechanism that integrates heuristic algorithms and genetic algorithms to efficiently locate the best resource combination for the construction simulation optimization. Results show that this new hybrid mechanism not only locates the optimal solution but also reduces tremendous computational efforts.
AB - Simulation is a powerful tool for planning and scheduling highly repetitive tasks in a construction project. However, sensitivity analysis has to be utilized to find the best resource combination to execute the construction tasks. By performing the sensitivity analysis, various resource combinations can be evaluated in terms of their effects on the operation's production and cost. The results of the sensitivity analysis can assist project managers in planning effective resource assignments based on their goals, such as maximizing the system's production rate or minimizing the system's unit cost. However, it is time-consuming to conduct the sensitivity analysis if there are a large number of resource alternatives available. This paper proposes a hybrid mechanism that integrates heuristic algorithms and genetic algorithms to efficiently locate the best resource combination for the construction simulation optimization. Results show that this new hybrid mechanism not only locates the optimal solution but also reduces tremendous computational efforts.
UR - http://www.scopus.com/inward/record.url?scp=10444251125&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=10444251125&partnerID=8YFLogxK
U2 - 10.1016/j.autcon.2004.07.014
DO - 10.1016/j.autcon.2004.07.014
M3 - Article
AN - SCOPUS:10444251125
VL - 14
SP - 85
EP - 98
JO - Automation in Construction
JF - Automation in Construction
SN - 0926-5805
IS - 1
ER -