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Akinci, B, Kiziltas, S, Ergen, E, Karaesmen, I Z and Keceli, F (2006) Modeling and Analyzing the Impact of Technology on Data Capture and Transfer Processes at Construction Sites: A Case Study. Journal of Construction Engineering and Management, 132(11), 1148–57.

Bai, Y and Burkett, W R (2006) Rapid Bridge Replacement: Processes, Techniques, and Needs for Improvements. Journal of Construction Engineering and Management, 132(11), 1139–47.

Col Debella, D and Ries, R (2006) Construction Delivery Systems: A Comparative Analysis of Their Performance within School Districts. Journal of Construction Engineering and Management, 132(11), 1131–8.

Gao, Z, Walters, R C, Jaselskis, E J and Wipf, T J (2006) Approaches to Improving the Quality of Construction Drawings from Owner’s Perspective. Journal of Construction Engineering and Management, 132(11), 1187–92.

Li, J, Moselhi, O and Alkass, S (2006) Forecasting Project Status by Using Fuzzy Logic. Journal of Construction Engineering and Management, 132(11), 1193–202.

Lu, M, Poon, C and Wong, L (2006) Application Framework for Mapping and Simulation of Waste Handling Processes in Construction. Journal of Construction Engineering and Management, 132(11), 1212–21.

Srour, I M, Haas, C T and Morton, D P (2006) Linear Programming Approach to Optimize Strategic Investment in the Construction Workforce. Journal of Construction Engineering and Management, 132(11), 1158–66.

  • Type: Journal Article
  • Keywords: Construction industry; Optimization; Training; Employees; Computer programming;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)0733-9364(2006)132:11(1158)
  • Abstract:
    The construction industry in the United States and other parts of the world has been facing several challenges, including a shortage of skilled workers. A review of the relevant body of knowledge indicates that one of the key reasons for this problem is the absence of human resource management strategies for construction workers at project, corporate, regional, or industry levels. This paper addresses the issues of workforce training and allocation on construction projects. It presents a framework to optimize the investment in, and to make the best use of, the available workforce with the intent to reduce project costs and improve schedule performance. A linear program model, entitled the Optimal Workforce Investment Model, is built to provide an optimization-based framework for matching supply and demand of construction labor most efficiently through training, recruitment, and allocation. Given a project schedule or demand profile and the available pool of workers, the suggested model provides human resource managers a combined strategy for training the available workers and hiring additional workers. The input data to the proposed model consists of a certain available labor pool, cost figures for training workers in different skills, the cost of hiring workers, hourly labor wages, and estimates of affinities between the different considered skills. The objective of the model is to minimize labor costs while satisfying project labor demands. Results from application of the model to typical situations are presented, and recommendations for future developments are made.

Telem, D, Laufer, A and Shapira, A (2006) Only Dynamics Can Absorb Dynamics. Journal of Construction Engineering and Management, 132(11), 1167–77.

Yu, A T W, Shen, Q, Kelly, J and Hunter, K (2006) Investigation of Critical Success Factors in Construction Project Briefing by Way of Content Analysis. Journal of Construction Engineering and Management, 132(11), 1178–86.

Zhang, X (2006) Markov-Based Optimization Model for Building Facilities Management. Journal of Construction Engineering and Management, 132(11), 1203–11.