DocumentCode :
2285888
Title :
Applying self-adaptive ant colony optimization for construction time-cost optimization
Author :
Li, Hui-Min ; Wang, Zhuo-fu
Author_Institution :
Inst. of Constr. Manage., Hohai Univ., Nanjing, China
fYear :
2009
fDate :
14-16 Sept. 2009
Firstpage :
283
Lastpage :
289
Abstract :
The time-cost optimization (TCO) problem is a multiobjective problem, which attempts to strike a balance between resource allocation costs and project schedule duration. In this paper, a self-adaptive ant colony optimization (SACO) with changing parameters based on information entropy has been employed to model time-cost optimization problem, which overcome the intrinsic weakness of premature of the basic ant colony optimization (ACO) by adjusting parameters according to mean information entropy of the ant system. A computer simulation with Matlab 7.0 based on a prototype example has been carried out on the basis of SACO for TCO problem. The test results show that the SACO for TCO model can generate a more optimal cost under the same duration and achieve a better Pareto front than other models. Therefore, the SACO can be regarded as a useful approach for solving construction project TCO problems.
Keywords :
Pareto optimisation; construction industry; costing; project management; resource allocation; scheduling; Matlab 7.0; Pareto front; construction project; information entropy; project schedule duration; resource allocation cost; self adaptive ant colony optimization; time-cost optimization problem; Ant colony optimization; Computer simulation; Conference management; Cost function; Engineering management; Information entropy; Mathematical model; Project management; Resource management; Stochastic processes; ant colony optimization; construction management; information entropy; multiobjective optimization; time-cost;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Management Science and Engineering, 2009. ICMSE 2009. International Conference on
Conference_Location :
Moscow
Print_ISBN :
978-1-4244-3970-6
Electronic_ISBN :
978-1-4244-3971-3
Type :
conf
DOI :
10.1109/ICMSE.2009.5317463
Filename :
5317463
Link To Document :
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