Fuzzy dynamic programming for optimized scheduling of repetitive construction projects

Uncertainty is an inherent characteristic of construction projects. Neglecting uncertainties associated with different input parameters in the planning stage could well lead to misleading and unrealistic project schedules. This research presents an algorithm for optimized scheduling of repetitive construction projects under uncertainty. The research utilizes fuzzy set theory to model uncertainties associated with different input parameters. It employs a dynamic programming algorithm that is especially tailored to accept input for different variables, perform all necessary computations and successfully deliver output, all in terms of fuzzy numbers. The algorithm has the ability to identify the optimum crew formation that would yield project least cost or project shortest duration according to the user preferences. A case study is drawn from literature and analyzed to demonstrate the algorithm's capabilities and to allow comparison of results to those generated using previous techniques.