A genetic algorithm-based method for look-ahead scheduling in the finishing phase of construction projects

Authors:
Ning Dong;Dongdong Ge;Martin Fischer;Zuhair Haddad
Affiliations:
Center for Integrated Facility Engineering (CIFE), Stanford University, 473 Via Ortega, Stanford, California, 94305, United States;Antai College of Economics and Management, Shanghai Jiao Tong University, 535 Fahua Zhen Road, Shanghai, 200052, China;Center for Integrated Facility Engineering (CIFE), Stanford University, 473 Via Ortega, Stanford, California, 94305, United States;Corporate Affairs and CIO, Consolidated Contractor's International Company (CCC), 62B Kifissias Ave, Amaroussion, Athens, 15110, Greece
Venue:
Advanced Engineering Informatics
Year:
2012

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Abstract

Genetic algorithms (GAs) are widely used in finding solutions for resource constrained multi-project scheduling problems (RCMPSP) in construction projects. In the finishing phase of a complex construction project, each room forms a confined space for crews to conduct a series of activities and can thus be considered as an individual sub-project. Generating the look-ahead schedule (LAS) which takes into account the limited resources available at the job site falls in the domain of RCMPSP. Therefore GAs can be used to address this scheduling problem and help construction managers to guide the daily work on site. However, current GAs do not consider three key practical aspects that the project planers and construction managers deal with frequently at the job sites: the engineering priorities of each individual sub-project, the zone constraint and the blocking constraint. By addressing these aspects, this paper proposes a GA-based method that takes them into account in the search process for optimum project duration and/or cost. Two examples are used for the discussion of the effectiveness of this method and to showcase its capability in project scheduling when the scale of a project increases.