Ordered Weighted Average optimization in Multiobjective Spanning Tree Problem
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Rework adversely impacts the performance of building projects. In this study, data were analyzed from 788 construction incidents in 40 Spanish building projects to determine the effects of project and managerial characteristics on rework costs. Finally, regression analysis was used to understand the relationships among contributing factors and to develop a model for rework prediction. Interestingly, the rework prediction model showed that only the original contract value (OCV) and the project location in relation to the company’s headquarters contributed to the regression model. Project type, type of organization, type of contract, and original contract duration (OCD), which represents the magnitude and complexity of a project, were represented by the OCV. This model for rework prediction based on original project conditions enables strategies to be put in place prior to the start of construction, to minimize uncertainties, to reduce impacts on project cost and schedule, and, thus, to improve productivity.
CitationFernandez, E., Pozo, M., Puerto Albandoz, J., Scozzari, A. Ordered Weighted Average optimization in Multiobjective Spanning Tree Problem. "European journal of operational research", 1 Agost 2017, vol. 260, núm. 3, p. 886-903.
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