Proceedings of the 5th International Symposium on Knowledge Acquisition and Modeling

Robust Optimization Analysis on Green Manufacturing Process Evaluation Based on Ordinal Interval Preference Information

Authors
Lin Yaqin, Guo Chunxiang
Corresponding Author
Lin Yaqin
Available Online June 2015.
DOI
https://doi.org/10.2991/kam-15.2015.55How to use a DOI?
Keywords
green manufacturing process; ordinal interval; robust optimization; mini-max regret criterion.
Abstract

With regard to the problem of ranking alternatives in green manufacturing process evaluation based on ordinal preference information with uncertain weight vector of attributes, a robust optimization analysis method is proposed. Firstly, the basic concepts and characters of ordinal interval preference information are introduced. Secondly, according to the probability matrix of ordinal preferences, a robust optimization model based on uncertain scenario with mini-max regret criterion is suggested. Then, a group preference gathered from individual preference is obtained by solving the model to acquire an overall robust solution. Finally, a numerical example is given to illustrate the feasibility of the method.

Copyright
© 2015, 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 5th International Symposium on Knowledge Acquisition and Modeling
Series
Advances in Intelligent Systems Research
Publication Date
June 2015
ISBN
978-94-62520-87-5
ISSN
1951-6851
DOI
https://doi.org/10.2991/kam-15.2015.55How to use a DOI?
Copyright
© 2015, 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  - Lin Yaqin
AU  - Guo Chunxiang
PY  - 2015/06
DA  - 2015/06
TI  - Robust Optimization Analysis on Green Manufacturing Process Evaluation Based on Ordinal Interval Preference Information
BT  - Proceedings of the 5th International Symposium on Knowledge Acquisition and Modeling
PB  - Atlantis Press
SP  - 202
EP  - 205
SN  - 1951-6851
UR  - https://doi.org/10.2991/kam-15.2015.55
DO  - https://doi.org/10.2991/kam-15.2015.55
ID  - Yaqin2015/06
ER  -