Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/22118
Title: Using improved genetic algorithms to facilitate time-cost optimization
Authors: Li, H 
Love, P
Issue Date: 1997
Source: Journal of construction engineering and management, 1997, v. 123, no. 3, p. 233-237
Abstract: Time-cost optimization problems in construction projects are characterized by the constraints on the time and cost requirements. Such problems are difficult to solve because they do not have unique solutions. Typically, if a project is running behind the scheduled plan, one option is to compress some activities on the critical path so that the target completion time can be met. As combinatorial optimization problems, time-cost optimization problems are suitable for applying genetic algorithms (GAs). However, basic GAs may involve very large computational costs. This paper presents several improvements to basic GAs and demonstrates how these improved GAs reduce computational costs and significantly increase the efficiency in searching for optimal solutions.
Publisher: American Society of Civil Engineers
Journal: Journal of construction engineering and management 
ISSN: 0733-9364
EISSN: 1943-7862
DOI: 10.1061/(ASCE)0733-9364(1997)123:3(233)
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