DocumentCode :
2261559
Title :
Multi-Objective Optimization in Construction Project Based on a Hierarchical Subpopulation Particle Swarm Optimization Algorithm
Author :
Wang, Weibo ; Feng, Quanyuan
Author_Institution :
Sch. of Inf. Sci. & Technol., Southwest Jiaotong Univ., Chengdu
Volume :
1
fYear :
2008
fDate :
20-22 Dec. 2008
Firstpage :
746
Lastpage :
750
Abstract :
Comprehensive trade-off control on construction time, cost and quality is main aspect of construction project management, and it is significant for improving the benefits of construction projects. This paper presents mathematical models for time, cost and quality separately, and a multi-objective optimization model for time-cost-quality trade-off optimization is set up by synthesizing weighted single-objective models. In a case study, comparing to standard particle swarm optimization (SPSO) and differential evolution algorithm (DE), the most satisfied decision results can be obtained by applying the hierarchical subpopulation particle swarm optimization algorithm (HSPSO) proposed in this paper to solve time-cost-quality trade-off problems. Finally, exhaustive enumeration is given to verify the effectiveness of the models and the feasibility of solution method.
Keywords :
construction industry; particle swarm optimisation; project management; construction cost; construction project management; construction quality; construction time; differential evolution algorithm; hierarchical subpopulation particle swarm optimization algorithm; mathematical model; multiobjective optimization; Ant colony optimization; Cost function; Genetic algorithms; Information science; Information technology; Integrated circuit modeling; Mathematical model; Particle swarm optimization; Project management; Quality management; Multi-objective Optimization; Particle Swarm Optimization algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Information Technology Application, 2008. IITA '08. Second International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3497-8
Type :
conf
DOI :
10.1109/IITA.2008.99
Filename :
4739671
Link To Document :
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