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Ahmed, S M, Sang, L P and Torbica, & M (2003) Use of Quality Function Deployment in Civil Engineering Capital Project Planning. Journal of Construction Engineering and Management, 129(04), 358–68.

Allouche, E N, Ariaratnam, S T and MacLeod, C W (2003) Software for Planning and Cost Control in Directional Drilling Projects. Journal of Construction Engineering and Management, 129(04), 446–53.

Attalla, M and Hegazy, T (2003) Predicting Cost Deviation in Reconstruction Projects: Artificial Neural Networks versus Regression. Journal of Construction Engineering and Management, 129(04), 405–11.

Chan, E H W and Tse, R Y C (2003) Cultural Considerations in International Construction Contracts. Journal of Construction Engineering and Management, 129(04), 375–81.

Chang, A S and Tsai, Y (2003) Engineering Information Classification System. Journal of Construction Engineering and Management, 129(04), 454–60.

Cheng, M and Ko, C (2003) Object-Oriented Evolutionary Fuzzy Neural Inference System for Construction Management. Journal of Construction Engineering and Management, 129(04), 461–9.

Fu, W K, Drew, D S and Lo, H P (2003) Competitiveness of Inexperienced and Experienced Contractors in Bidding. Journal of Construction Engineering and Management, 129(04), 388–95.

Hassim, S, Kadir, M R A, Lew, Y and Sim, Y (2003) Estimation of Minimum Working Capital for Construction Projects in Malaysia. Journal of Construction Engineering and Management, 129(04), 369–74.

Hegazy, T and Petzold, K (2003) Genetic Optimization for Dynamic Project Control. Journal of Construction Engineering and Management, 129(04), 396–404.

  • Type: Journal Article
  • Keywords: Optimization; Algorithms; Project management; Computer applications; Construction management; optimisation; construction industry; project management; computer aided analysis; cost optimal control; civil engineering;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)0733-9364(2003)129:4(396)
  • Abstract:
    This paper presents a comprehensive model for cost optimization and dynamic project control. The model incorporates an integrated formulation for estimating, scheduling, resource management, and cash-flow analysis. The basic premise of the model is to allocate optional construction methods for each activity, varying from cheap and lengthy to expensive and short. Using a genetic algorithms procedure for total cost optimization, the model considers the actual progress of activities and optimizes the schedule of remaining ones (by determining the best combination of construction methods) so that project constraints are respected. The model, as such, is usable not only at the planning stage but also during construction. A description of the model and its application on an example project are provided in this paper. In addition, the paper introduces the recently emerged critical chain method for project control and describes an effort to incorporate some of its features into the earned-value analysis used in the proposed model.

Ibbs, C W, Kwak, Y H, Ng, T and Odabasi, A M (2003) Project Delivery Systems and Project Change: Quantitative Analysis. Journal of Construction Engineering and Management, 129(04), 382–7.

Lee, S and Halpin, D W (2003) Predictive Tool for Estimating Accident Risk. Journal of Construction Engineering and Management, 129(04), 431–6.

Lu, M and Li, H (2003) Resource-Activity Critical-Path Method for Construction Planning. Journal of Construction Engineering and Management, 129(04), 412–20.

Navon, R and Goldschmidt, E (2003) Can Labor Inputs be Measured and Controlled Automatically?. Journal of Construction Engineering and Management, 129(04), 437–45.

Warszawski, A (2003) Analysis of Costs and Benefits of Tall Buildings. Journal of Construction Engineering and Management, 129(04), 421–30.