Solving 0-1 Knapsack Problem by Greedy Degree and Expectation Efficiency
- Submitting institution
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University of Hertfordshire
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 16421815
- Type
- D - Journal article
- DOI
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10.1016/j.asoc.2015.11.045
- Title of journal
- Applied Soft Computing
- Article number
- -
- First page
- 94
- Volume
- 41
- Issue
- -
- ISSN
- 1568-4946
- Open access status
- Out of scope for open access requirements
- Month of publication
- April
- Year of publication
- 2016
- URL
-
-
- Supplementary information
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-
- 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
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4
- Research group(s)
-
-
- Citation count
- 22
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper is predominantly theoretical work, which has impact on both theory and applications. Theoretically, it has inspired metaheuristics developed for solving the 0-1 knapsack problem, e.g., whale optimization by Prof Arun Kumar Sangaiah in VIT University, India, and the binary dragonfly algorithm by Prof Mohamed Abdel-Basset in Zagazig University, Egypt. Practically, it has motivated problem solving in applications such as urban flood control by Prof George Q. Huang in University of Hong Kong, and Pressure Testing During Reentry Operation of Deepwater Drilling Riser System by Prof Guoming Chen in China University of Petroleum (East China).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -