Abstract

The reassignment of crews on a construction project in response to changes occurs on a frequent basis. The factors that affect the crew reassignment decision can be myriad and most are not known with certainty. This research addresses the need for a decision support model to assist construction managers with the crew reassignment problem. The model design makes use of certainty factors in a decision tree structure. The research helped to determine the elements in the decision tree, the appropriate combination rules to use with the certainty factors, and the method for combining the certainty factors and costs to develop a measure of cost for each decision option. The research employed surveys, group meetings, and individual interviews of experienced construction managers and superintendents to investigate the current methods used by decision makers to identify and evaluate the key elements of the construction crew reassignment decision. The initial research indicated that the use of certainty factors was preferred over probabilities for representing the uncertainties. Since certainty factors have not been used in a traditional decision tree context, a contribution of the research is the development and testing of techniques for combining certainty factors, durations, and costs in order to represent the uncertainty and to emulate the decision process of the experts interviewed. The developed model provides the decision maker with an estimate of upper and lower bounds of costs for each crew reassignment option. The model was applied contemporaneously to six changes on three ongoing construction projects to test the model and assess its usefulness. The model provides a previously unavailable tool for the prospective identification and estimation of productivity losses and potential costs that emanate from changes. The users indicated the model process resulted in concise and complete compilations of the elements of the crew reassignment decision and that the model outputs were consistent with the users' expectations.

Notes

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Graduation Date

2004

Semester

Fall

Advisor

Pet-Armacost, Julia

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Industrial Engineering and Management Systems

Format

application/pdf

Identifier

CFE0000297

URL

http://purl.fcla.edu/fcla/etd/CFE0000297

Language

English

Release Date

October 2018

Length of Campus-only Access

None

Access Status

Doctoral Dissertation (Open Access)

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