Source code for the article: Time/sequence-dependent scheduling: the design and evaluation of a general purpose tabu-based adaptive large neighbourhood search algorithm
Datacite citation style:
He, Lei; de Weerdt, Mathijs; Yorke-Smith, Neil (2019): Source code for the article: Time/sequence-dependent scheduling: the design and evaluation of a general purpose tabu-based adaptive large neighbourhood search algorithm. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/uuid:3a23b216-3762-4a61-ba2c-d3df6dc53268
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Dataset
In intelligent manufacturing, it is important to schedule orders from customers efficiently. Make-to-order companies may have to reject or postpone orders when the production capacity does not meet the demand. Many such real-world scheduling problems are characterised by processing times being dependent on the start time (time dependency) or on the preceding orders (sequence dependency), and typically have an earliest and latest possible start time. We introduce and analyze four algorithmic ideas for this class of time/sequence-dependent over-subscribed scheduling problems with time windows: a novel hybridization of adaptive large neighbourhood search (ALNS) and tabu search (TS), a new randomization strategy for neighbourhood operators, a partial sequence dominance heuristic, and a fast insertion strategy.
This dataset contains the source code of our hybrid algorithm: ALNS/TPF. If you use this code, please cite the following paper: He L , De Weerdt M , Yorke-Smith N. Time/sequence-dependent scheduling: the design and evaluation of a general purpose tabu-based adaptive large neighbourhood search algorithm[J]. Journal of Intelligent Manufacturing, 2019, DOI: 10.1007/s10845-019-01518-4.
history
- 2019-12-28 first online, published, posted
publisher
4TU.Centre for Research Data
format
media types: application/octet-stream, application/x-dosexec, application/x-font-ttf, application/zip, text/plain, text/xml
references
- https://aaai.org/ojs/index.php/ICAPS/article/view/3475
- https://doi.org/10.1007/s10845-019-01518-4
- https://doi.org/10.1016/j.cie.2019.106102
- https://doi.org/10.4121/uuid:1a4e5895-7dae-4b6a-9315-a9e8cb463d73
- https://doi.org/10.4121/uuid:1ad913e4-2518-44c3-b497-fb106cf84e05
- https://doi.org/10.4121/uuid:c3623076-a1ac-4103-ad31-3068a28312f9
funding
- China Hunan Provincial Innovation Foundation for Postgraduate, CX2018B020
- China Scholarship Council, 201703170269
organizations
TU Delft, Faculty of Faculty of Engineering, Mathematics and Computer Science (EEMCS)
DATA
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