Abstract—This paper provide a solution approach for planning, scheduling and managing project efforts where there is significant uncertainty in the duration, resource requirements and outcomes of individual tasks. Our approach yields a nonlinear (GA) optimization model for allocation of resources and available time to tasks. This formulation represents a significantly different view of project planning from the one implied by traditional project scheduling, and focuses attention on important resource allocation decisions faced by project managers. The model can be used to maximize any of several possible performance measures for the project as a whole. We include a small computational example that focuses on maximizing the probability of successful completion of a project whose tasks have uncertain outcomes. The resource allocation problem formulated here has importance and direct application to the management of a wide variety of project-structured efforts where there is significant uncertainty.

Index Terms—Project scheduling, Resource constraints projects, Genetics algorithms, Uncertainty

Cite: Ahmed Farouk, Khaled El Kilany, and Fady Safwat, "Genetic Algorithm for Project Scheduling and Resource Allocation under Uncertainty," International Journal of Mechanical Engineering and Robotics Research, Vol.2 No.3, pp. 1-14, July 2013.