Resource Constrained Project Scheduling With Dynamic Disruption Recovery

Abstract

Resource-constrained project scheduling is one of the most widely studied research problems. Although a large number of algorithms have been developed for solving these problems, many of them ignored several practical issues such as resource unavailability and disruptions, and a recovery plan for after a disruption. This paper investigates different cost-effective measures for project scheduling problems under resource disruptions, in which the disrupted resources are dynamically recovered as the project progresses. Firstly, a new proactive scheduling technique is proposed to determine the make-span with an emphasis on maximizing the floating resources that can be used as a buffer to handle any future disruption effectively. Secondly, we introduce a bi-objective approach for reactive scheduling if a disruption occurs, in which both the revised make-span and recovery cost are minimized. Both proactive and reactive models are solved using a specially designed multi-method based evolutionary optimization algorithm, with the results obtained showing the benefits of the proposed method in comparison to state-of-the-art algorithms.

Keywords

• Project scheduling
• dynamic disruption
• genetic algorithm
• differential evolution