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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.

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.

  • Type: Journal Article
  • Keywords: Assets; Facilities; Deterioration; Optimization; Service life; Stochastic processes; Markov process;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)0733-9364(2006)132:11(1203)
  • Abstract:
    An effective and efficient building facilities management system calls for a systematic performance-based methodology. This paper proposes an integer-programming model based on the Markov decision process: Markov chains are used to model the change of condition index, a consistent scale to measure building performance, and integer programming employed to optimize annual management actions and annual budget allocation, subject to various types of constraints. A wide scope of useful outputs can be obtained from this model. This includes: (1) annual management actions to take; (2) annual budget allocation; (3) the expected condition index (CI) values at the beginning of each year before and after management actions are taken; (4) the expected annual performance levels; and (5) sensitivity analysis and corresponding outputs to different budget scenarios, for all the elements, components, systems and buildings of a building network and for each year over a long time horizon. As a general model, it can be applied in any type of building network.