期刊
APPLIED MATHEMATICAL MODELLING
卷 50, 期 -, 页码 314-332出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.apm.2017.05.034
关键词
Scheduling; Learning effect; Aging effect; Computational complexity; Strongly NP-hard; Parallel branch and bound
资金
- Polish Ministry of Science and Higher Education under Iuventus Plus Programme [P2014 040673]
Although the single machine scheduling problem to minimize the total weighted completion times with the sum-of-processing time based learning or aging effects have been known for a decade, it is still an open question whether these problems are strongly NP hard. We resolve this issue and prove them to be strongly NP-hard with the learning effect as well as with the aging effect. Furthermore, we construct an exact parallel branch and bound algorithm for the problem with general sum-of-processing time based models, which can solve optimally moderate problem instances in reasonable time. (C) 2017 Elsevier Inc. All rights reserved.
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