A Fuzzy Ant Colony Approach to Fully Fuzzy Resource Constrained Project Scheduling Problem

Abstract

In this paper a fully fuzzy resource constrained project scheduling model is presented in which activities durations and resource consumptions of activities are estimated by fuzzy numbers. To increase compatibility between presented model and real world situations, availability of resources are predicted using fuzzy numbers. Taking into account the concept of “fuzzy decision making in fuzzy environment” and regarding the fact that all parameters of the presented model are uncertain, fuzzy scheduling is considered for this problem in which activities start and finish times are calculated in form of triangular fuzzy numbers. Also, due to this fact that resource constrained project scheduling problems (RCPSPs) belong to the class of the NP-hard problems, a solution approach is developed using Ant Colony Optimization (ACO) algorithm. Regarding fuzzy nature of decision variables, some modifications are made to ACO to make it compatible with the presented fuzzy RCPS model. To illustrate flexibility of the developed model and efficiency of the presented solution approach, some numerical examples are provided.