Applying fuzzy goal programming to project management decisions with multiple goals in uncertain environments

In real-life situations, the project manager must handle multiple conflicting goals and these conflicting goals are normally fuzzy owing to information is incomplete and unavailable. This study develops a two-phase fuzzy goal programming (FGP) method for solving the project management (PM) decision problems with multiple goals in uncertain environments. The original multi-objective linear programming (MOLP) model designed here attempts to simultaneously minimize total project costs, total completion time and total crashing costs with reference to direct costs, indirect and contractual penalty costs, duration of activities and the constraint of available budget. An industrial case is implemented to demonstrate the feasibility of applying the proposed two-phase FGP method to practical PM decisions. The contribution of this study lies in presenting a fuzzy mathematical programming methodology to fuzzy multi-objective PM decisions, and provides a systematic decision-making framework that facilitates the decision maker to interactively adjust the search direction until the preferred efficient solution is obtained.