Back to Search Start Over

A new proactive and reactive approach for resource-constrained project scheduling problem under activity and resource disruption: a scenario-based robust optimization approach.

Authors :
Khoshsirat, Maziar
Mousavi, Seyed Meysam
Source :
Annals of Operations Research. Jul2024, Vol. 338 Issue 1, p597-643. 47p.
Publication Year :
2024

Abstract

This paper introduces a novel two-phase framework for designing a proactive–reactive scheduling model in the multi-mode resource-constrained project scheduling problem under disruptions. The proactive phase involves constructing a resilient baseline scheduling model using a mixed-integer linear programming model. This phase contributes to a multi-objective model that minimizes the project completion time and total project cost while maximizing resilience criteria. In this context, resilience refers to allocating float time to project activities to protect their start and finish times against future disruptions as much as possible. The reactive phase involves a bi-objective mathematical model that mitigates the impact of disruptions through preempt-repeat, preempt-resume, and activity-crashing strategies. Real-world projects involve many uncertain parameters that can negatively affect the optimization of rescheduling problems if overlooked. Therefore, for the first time, a scenario-based robust optimization approach is proposed to cope with the uncertainty of the reactive phase. Additionally, a novel hybrid multi-objective method based on goal programming is introduced to solve the proposed multi-objective model. Finally, to demonstrate the capability of the proposed approach, an oil and gas project in Iran is regarded as a real case study. The results indicate that the negative impact of disruptions on the makespan and total cost of the project can be largely mitigated by considering resilience criteria in the proactive phase and preempt-repeat, preempt-resume, and activity-crashing strategies in the reactive phase. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02545330
Volume :
338
Issue :
1
Database :
Academic Search Index
Journal :
Annals of Operations Research
Publication Type :
Academic Journal
Accession number :
178444645
Full Text :
https://doi.org/10.1007/s10479-024-05895-9