Supplementary data for the article: Order Acceptance and Scheduling with Sequence-dependent Setup Times: a New Memetic Algorithm and Benchmark of the State of the Art

Datacite citation style:
He, Lei; Guijt, A. (Arthur); de Weerdt, Mathijs; Xing, L. (Lining); Yorke-Smith, Neil (2019): Supplementary data for the article: Order Acceptance and Scheduling with Sequence-dependent Setup Times: a New Memetic Algorithm and Benchmark of the State of the Art. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/uuid:c3623076-a1ac-4103-ad31-3068a28312f9
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
The Order Acceptance and Scheduling (OAS) consists of simultaneously selecting a subset of orders to be processed as well as determining the associated schedule. A common generalization includes sequence-dependent setup times and time windows. We propose a novel memetic algorithm for this problem, called Sparrow. The dataset contains the source code of Sparrow, as well as our implementation of two state-of-the-art algorithms for the OAS problem from the literature. It also contains some new benchmark instances with more realistic properties. "If you use this data and/or code, please cite the following paper: He L , Guijt A , De Weerdt M , et al. Order Acceptance and Scheduling with Sequence-dependent Setup Times: a New Memetic Algorithm and Benchmark of the State of the Art[J]. Computers & Industrial Engineering, 2019, 138."
history
  • 2019-10-31 first online, published, posted
publisher
4TU.Centre for Research Data
format
media types: application/octet-stream, application/x-dosexec, application/zip, text/plain, text/xml
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)
contributors
  • Cesaret, B. (Bahriye) orcid logo
  • O─čuz, C. (Ceyda) orcid logo
  • Salman, F.S. (F. Sibel) orcid logo

DATA

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