Application of an Improved Granular Algorithm in C2 Design

DOI

10.2991/ameii-15.2015.340How to use a DOI?

Keywords

command and control; granular algorithm; optimization.

Abstract

With the increasing scale of issue, the list planning performance remarkably decreases in the three-step method. To solve this issue, an improved granular algorithm is proposed in this paper for the C2 model design. At first, the adaptability measurement of model is optimized from the perspective of coarse granularity. Then, the completion period of task is optimized from the perspective of fine granularity. Thus, the two objectives can be optimized at the same time to some extent. According to case analysis and comparative test, this method can be used to simplify the complexity of solution and get ideal optimization results. Therefore, it is of good performance.

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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TY  - CONF
AU  - Shuai Chen
AU  - Xuejun Ren
AU  - Wenjing Shao
PY  - 2015/04
DA  - 2015/04
TI  - Application of an Improved Granular Algorithm in C2 Design
BT  - Proceedings of the International Conference on Advances in Mechanical Engineering and Industrial Informatics
PB  - Atlantis Press
SP  - 1833
EP  - 1837
SN  - 2352-5401
UR  - https://doi.org/10.2991/ameii-15.2015.340
DO  - 10.2991/ameii-15.2015.340
ID  - Chen2015/04
ER  -