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A buffer allocation evolutionary algorithm for resource-constrained projects with activity clusters
Cao, Fangfang Servranckx, Tom He, Zhengwen
Cao, Fangfang
Servranckx, Tom
He, Zhengwen
Publication Type
Journal article with impact factor
Editor
Supervisor
Publication Year
2025-10
Journal
Journal of Scheduling
Book
Publication Volume
28
Publication Issue
5
Publication Begin page
483
Publication End page
511
Publication Number of pages
Collections
Abstract
We propose a novel approach for sizing the activity buffers in the project by clustering similar activities and allocating the buffers using a unique attribute in each cluster. Since the number of clusters as well as the assignment of attributes to these clusters has an impact on the buffer sizing, the problem is solved using an adapted multifactorial evolutionary algorithm (aMFEA) in which multiple buffer allocation problems (BAPs) are solved simultaneously. Several decoding schemes are compared to improve the synergies between the different BAPs and the evolutionary operators. The results show the added value of the evolutionary components of the aMFEA and show that the proposed approach is superior to existing benchmarking procedures. Furthermore, the solution quality improves with an increasing number of clusters, while the solution quality goes down again as the number of clusters becomes too large. From a practical perspective, this study highlights the need to identify good activity attributes that are linked to the buffer sizing decisions and the importance of activity clustering in order to reduce the time and effort needed for better buffer sizing decisions.
Research Projects
Organizational Units
Journal Issue
Keywords
Buffer Allocation Problem, Clustering, Multifactorial evolutionary algorithm, Project Scheduling