Genetic Algorithm for Project Scheduling and Resource Allocation under Uncertainty

Abstract

The objective of the present work is to construct a mathematical model to solve the problem of project scheduling and allocation of resources under uncertainty in duration and resource requirements of individual tasks. The model is composed of an objective function which maximizes the probability of success to complete the project in a given time window and a set of constraints that satisfy the precedence relationships and the resource constraints. The proposed model considers the non-availability of the total number of resources from the beginning of the project. A Genetic Algorithm is developed to solve the proposed model, and a visual basic program under Excel was written to solve the Genetic Algorithm. The proposed model was validated through two case studies of different sizes (number of activities). The proposed approach proved to be efficient in solving the problem and realizes better solution than other approaches found in the literature, especially the models based on non linear optimization. Keywords: Project Management and Scheduling, Resource-Constraints, Genetic Algorithms, uncertainty.