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MIP-based solution approaches for multi-site resource-constrained project scheduling

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BORIS DOI
10.48620/91121
Publisher DOI
10.1007/s10479-022-05109-0
Description
The execution of a project is often distributed among multiple sites. The planning of such a project includes selecting a specific site for the execution of each of the project’s activities and allocating the available resource units to the execution of these activities over time. While some resource units are available at a certain site only, others can be moved across sites. Given the spatial distance between sites, transportation times arise if a resource unit must be transported from one site to another or if the output of an activity must be transported to another site. This planning problem has been introduced in recent literature as the multi-site resource-constrained project scheduling problem. We present a continuous-time model and devise a matheuristic for this planning problem. The continuous-time model uses, among others, binary variables to impose a sequence between activities assigned to the same resource units. In the matheuristic, the binary restrictions on these variables are initially relaxed and iteratively restored for the subset of activities scheduled in the current iteration. We compare the performance of the continuous-time model and the matheuristic to the performance of a discrete-time model and several metaheuristics from the literature using two sets of test instances from the literature. Both the continuous-time model and the matheuristic derive on average superior solutions in shorter average running times than the reference approaches.
Date of Publication
2024-06
Publication Type
Article
Language(s)
en
Contributor(s)
Bigler, Tamaraorcid-logo
Chair of Quantitative Methods in Business Administration
Gnägi, Mario
Teaching Staff, Faculty of Business, Economics and Social Sciences
Trautmann, Norbert
Chair of Quantitative Methods in Business Administration
Additional Credits
Chair of Quantitative Methods in Business Administration
Teaching Staff, Faculty of Business, Economics and Social Sciences
Series
Annals of Operations Research
Publisher
Springer
ISSN
0254-5330
1572-9338
Access(Rights)
open.access
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