A genetic algorithm for solving fuzzy resource-constrained project scheduling

This paper studies the resource-constrained project scheduling problem with fuzzy activity duration and fuzzy deadline. On the basis of the concept of schedule robustness for fuzzy deadline and fuzzy project makespan, we seek for a schedule that maximizes the schedule robustness. First, An efficient genetic algorithm (GA) based on activity list representation is proposed for solving this problem, the performance of our GA and GA based on the priority value representation is compared. Second, we study the impact for the two different weak comparison rules (integral value method, distance method) in the performance of GA. The computational experiment shows that the performance of the proposed GA is better than GA appearing in the literature, there is no significant difference between the two weak comparison rules on the Performance of the algorithm.