A hybrid chemical reaction optimization scheme for task scheduling on heterogeneous computing systems
- Submitting institution
-
The University of Warwick
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 6000
- Type
- D - Journal article
- DOI
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10.1109/TPDS.2014.2385698
- Title of journal
- IEEE Transactions on Parallel and Distributed Systems
- Article number
- -
- First page
- 3208
- Volume
- 26
- Issue
- 12
- ISSN
- 1045-9219
- Open access status
- Out of scope for open access requirements
- Month of publication
- December
- Year of publication
- 2015
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
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D - Data Science, Systems and Security
- Citation count
- 83
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This highly cited work, joint with distinguished scholar and IEEE Fellow Li from SUNY, and published in a top journal in the field, provided a new evolution-based method to schedule complex tasks on heterogeneous systems. It has enabled much subsequent research, leading to applications in areas including multi-compartment vehicle routing (University of Manitoba, ASC 2015), public distribution systems (IIT Kharagpur, CIE 2017), scheduling in asymmetric multi-core systems (ARM, TPDS 2016), and supply chains (Isfahan University of Technology, ASC 2016). This work has also underpinned further collaborative research with WinHong Information Technology, Guangzhou, China (contact: Mr GQ Zhang, zhanggq@winhong.com).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -