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Advances in Production Engineering & Management

Archives > Volume 19 | Number 4 | December 2024 > pp 489–511

Advances in Production Engineering & Management
Volume 19 | Number 4 | December 2024 | pp 489–511

https://doi.org/10.14743/apem2024.4.520

An algorithmic review of the technological progress and milestones in resource-constrained project planning
Pourhejazy, P.; Ying, K.-C.; Cheng, C.-Y.
ABSTRACT AND REFERENCES (PDF)  |  FULL ARTICLE TEXT (PDF)

A B S T R A C T
Engineering, procurement, and construction projects are time-intensive and subject to resource constraints. Modern project planning software requires optimization algorithms to schedule tasks while considering resource availability. A comprehensive review of the optimization algorithms used in project planning has not yet been conducted. This study seeks to bridge the gap through an algorithmic review of the Resource-constrained Project Scheduling Problems (RCPSPs) literature and investigates the following research questions: What are the milestones on the main development trajectory of optimization algorithms for solving RCPSPs? How might this influence future advancements in the field? To answer these questions, the Main Path Analysis (MPA) method is employed to review the development trajectory and milestones from over 1100 project scheduling articles published between 1980 and 2024. Cluster Analysis (CA) complements the investigations by identifying the prevalent research themes, mathematical features, and solution algorithms. Recommendations for future research directions, supported by the systematic review, conclude the study. This review provides a reference for project management researchers focused on industrial applications of project scheduling problems.

A R T I C L E   I N F O
Keywords • Project management; Task scheduling; Resource constraint; Multi-objective optimization; Evolutionary computation; Swarm intelligence; Metaheuristics; Main path analysis; Cluster analysis
Corresponding authorPourhejazy, P. , Ying, K.-C.
Article history • Received 27 October 2024, Revised 6 December 2024, Accepted 17 December 2024
Published on-line • 30 December 2024

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