Two-tuple Linguistic Multi-attribute Decision-making based on Grey Target Theory
- DOI
- 10.2991/meic-14.2014.154How to use a DOI?
- Keywords
- grey target theory; two-tuple linguistic;multi-attribute decision- making;attribute weights;bull’s-eye related coefficient
- Abstract
Nowadays, selection of an optimal investment program has become a challenging task for the decision makers in the Electric Power Company. Investment program selection for a company can be viewed as a complicated multi-criteria decision making (MCDM) problem which requires consideration of selection attributes. Moreover, decision makers tend to use multi-granularity linguistic term sets for expressing their assessments because of their different backgrounds and preferences, some of which may be uncertain and incomplete. Therefore, this paper studies the multi-attirbute decision-making problem under two-tuple linguistic environment and proposes a new approach based on grey target theory. A new two-tuple linguistic bull’s-eye is defined and the two-tuple linguistic bull’s-eye related coefficient is derived consequently. Then, a new optimization model is provided by applying maximize deviation principle to determine the attributes weights. The order of alternatives is listed by comparing the two-tuple linguistic bull’s-eye relative related degree. Finally, an example of power communication resources investment illustrates the applicability of the proposed method.
- Copyright
- © 2014, 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 - Bo Sui AU - Lijuan Yan AU - Yufang Yang AU - Jianwei Gao PY - 2014/11 DA - 2014/11 TI - Two-tuple Linguistic Multi-attribute Decision-making based on Grey Target Theory BT - Proceedings of the 2014 International Conference on Mechatronics, Electronic, Industrial and Control Engineering PB - Atlantis Press SP - 688 EP - 692 SN - 2352-5401 UR - https://doi.org/10.2991/meic-14.2014.154 DO - 10.2991/meic-14.2014.154 ID - Sui2014/11 ER -