Application of fuzzy mathematical programming to imprecise project management decisions

In real-world project management (PM) decisions, the input data and environmental coefficients are generally imprecise/fuzzy because of incompleteness and unavailability of relevant information over the project planning horizon. This work aims to present a fuzzy mathematical programming approach to solve imprecise PM decision problems with fuzzy goal and fuzzy cost coefficients. The designed PM decision model attempts to minimize total project costs with reference to direct costs, indirect costs, contractual penalty costs, duration of activities and the constraint of available budget. The proposed approach achieves greater computational efficiency by employing the simplified triangular fuzzy number to represent imprecise goal and cost coefficients, and provides a systematic framework that facilitates the decision-making process, enabling a decision maker to interactively modify the imprecise data and related parameters until a satisfactory solution is obtained. An industrial case is implemented to demonstrate the feasibility of applying the proposed approach to practical PM problems. The computational methodology developed in this work can easily be extended to any other situations and can handle the realistic PM decisions in fuzzy environments.