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Applying Pareto Ranking and Niche Formation to Genetic Algorithm-Based Multiobjective Time–Cost Optimization

Applying Pareto Ranking and Niche Formation to Genetic Algorithm-Based Multiobjective Time–Cost Optimization

Authors :
Mohan M. Kumaraswamy
S. Thomas Ng
Daisy X. M. Zheng
Source :
Journal of Construction Engineering and Management. 131:81-91
Publication Year :
2005
Publisher :
American Society of Civil Engineers (ASCE), 2005.

Abstract

Time–cost optimization (TCO) is one of the greatest challenges in construction project planning and control, since the optimization of either time or cost, would usually be at the expense of the other. Although the TCO problem has been extensively examined, many research studies only focused on minimizing the total cost for an early completion. This does not necessarily convey any reward to the contractor. However, with the increasing popularity of alternative project delivery systems, clients and contractors are more concerned about the combined benefits and opportunities of early completion as well as cost savings. In this paper, a genetic algorithms ( GAs ) -driven multiobjective model for TCO is proposed. The model integrates the adaptive weight to balance the priority of each objective according to the performance of the previous “generation.” In addition, the model incorporates Pareto ranking as a selection criterion and the niche formation techniques to improve popularity diversity. Based on the pr...

Details

ISSN :
19437862 and 07339364
Volume :
131
Database :
OpenAIRE
Journal :
Journal of Construction Engineering and Management
Accession number :
edsair.doi...........6a9e72f0386a28136b5ecce31fb7b431
Full Text :
https://doi.org/10.1061/(asce)0733-9364(2005)131:1(81)