The resource-constrained project scheduling problem belongs to the class of decision problems that have much application in real-life projects. A variety of solution approaches, such as deterministic and stochastic methods, have been applied to solve this problem without complete success. We now use fuzzy theory that provides a precise and practical solution method....[ Read more ]

The resource-constrained project scheduling problem belongs to the class of decision problems that have much application in real-life projects. A variety of solution approaches, such as deterministic and stochastic methods, have been applied to solve this problem without complete success. We now use fuzzy theory that provides a precise and practical solution method.

We first identify thirteen typical activity priority rules used in the resource-constrained project scheduling problem. The rules are classified into four groups according to their definitive characteristics. Our objective is to check the performance of these rules in minimizing the project completion time. Our procedure is as follows: We randomly generate realizations of projects by the standard project generator ProGen. Our generation is based on different levels of the four project parameters: project size, network complexity, resource factor, and resource strength. The activity durations of each of the project realization are then fuzzified. Based on the fuzzy algebra, including fuzzy addition, fuzzy averaging, and comparison and defuzzification of fuzzy numbers, we propose a fuzzy parallel procedure for the thirteen rules that helps to identify the (fuzzified) project completion times of each of the project realizations. The average project completion times are then thoroughly analyzed statistically. The relative performance ranks of the rules are identified for different parameter levels. Following this approach, we know which rules to use for a project with a given set of project parameter values.