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.
Highlights
A project is defined as a collection of linked activities where all the activities must be completed to finish it
Using the maximum number of generations as a stopping criterion may not be fair as different algorithms use different heuristics which each perform a number of iterations
The proactive model is formulated as a single objective optimization problem, in which the make-span is minimized with float resources (FRs) during the later stage of the project horizon being maximized to alleviate the initial make-span after a disruption in resource availability
Summary
A project is defined as a collection of linked activities where all the activities must be completed to finish it. To handle the disruptions in resource availability, a few solution approaches have been introduced, in which the problems are solved based on two different scenarios: (i) proactive, where the scheduling is generated before a disruption takes place without having any knowledge about it, and (ii) reactive, which is done after a disruption occurs. Zaman et al.: Resource Constrained Project Scheduling With Dynamic Disruption Recovery activities discarding any partial completion (i.e. by restarting from the beginning), and the later reschedules the affected activities while considering that partial completions that occurred before a disruption occurs, continue on from where they left off In both cases, it is assumed that the disruption would be recovered from after a certain number of time units.
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