Proceedings of the 2013 International Academic Workshop on Social Science

The research of some single-machine scheduling problems

Authors
Zhigao Liao, Xiaojing Zhao
Corresponding Author
Zhigao Liao
Available Online October 2013.
DOI
https://doi.org/10.2991/iaw-sc.2013.193How to use a DOI?
Keywords
Scheduling; position-dependent learning effect model; time-dependent learning effect mode
Abstract

In this paper, we develop a new scheduling model with learning effects where the actual processing time of a job is not only a function of the total normal processing times of the jobs already processed, but also a function of the job’s scheduled position. We show that the single-machine scheduling problems to minimize make span and total complete time are still polynomially solvable under the proposed model. We further show that the single-machine scheduling problems minimizing the weighted sum of completion times and minimizing the maximum lateness are also polynomially solvable under certain conditions.

Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2013 International Academic Workshop on Social Science
Series
Advances in Intelligent Systems Research
Publication Date
October 2013
ISBN
978-90-78677-84-0
ISSN
1951-6851
DOI
https://doi.org/10.2991/iaw-sc.2013.193How to use a DOI?
Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Zhigao Liao
AU  - Xiaojing Zhao
PY  - 2013/10
DA  - 2013/10
TI  - The research of some single-machine scheduling problems
BT  - Proceedings of the 2013 International Academic Workshop on Social Science
PB  - Atlantis Press
SP  - 852
EP  - 855
SN  - 1951-6851
UR  - https://doi.org/10.2991/iaw-sc.2013.193
DO  - https://doi.org/10.2991/iaw-sc.2013.193
ID  - Liao2013/10
ER  -