Fuzzy Multiple Attributes Decision-Making Hybrid Model for Selecting Aircraft Baseline Scenario

R.B. Wang; L.X. Gu

doi:10.4028/www.scientific.net/AMM.743.30

Paper Titles

Design and Optimization of Clutch Hydraulic Shift Control System in Automatic Transmissions with Failure Protection Function
p.11

The Common Fault Analysis and the Solution of CKA6140 NC Lathe
p.17

Singularity and Dexterity Analysis of the Test Tilter for the Optical Landing Aid System
p.22

Analysis on Current Technical Status and Development of Tumbler Screening Machines in China and Abroad
p.26

Fuzzy Multiple Attributes Decision-Making Hybrid Model for Selecting Aircraft Baseline Scenario
p.30

Design of a Horizontal Axis Turbine Marine Energy Generation System
p.37

Adaptive Optimization Design of Machining Center Tool Changing Manipulator
p.43

Fatigue Damage of a Cutter Used for Cutting Cashew Nut under Random Load
p.49

Key Technologies Research of Helicopter Transmissions
p.55

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 743Fuzzy Multiple Attributes Decision-Making Hybrid...

Fuzzy Multiple Attributes Decision-Making Hybrid Model for Selecting Aircraft Baseline Scenario

Abstract:

Expertise or certain performance metrics information was often separately considered to model the Aircraft baseline scenario preferential problem in a traditional way, with one-sidedness and subjective. This paper focus on baseline scenario preferential problem in aircraft conceptual design, proposed a hybrid fuzzy decision merit model with synthesizing the description and numerical fuzzy indicators and using interval theory to model the fuzziness of each attribute. Proposed the preference information method based on multi-level expertise interval scale to model description fuzzy indicators and grey incidence analysis to model numerical fuzzy indicators, induced objective information entropy to increase the discrimination degree among group information, and then established a hybrid fuzzy interval multi-attribute decision model based on expertise, grey scale and objective information entropy, by constructing the Lagrangian function to solve each attribute weights. Applied it to the aircraft baseline scenario preferred example, to verify its feasibility and effectiveness.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volume 743)

Pages:

30-36

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.743.30

Citation:

Cite this paper

Online since:

March 2015

Authors:

R.B. Wang*, L.X. Gu

Keywords:

Benchmark Scheme, Conceptual Design, Decision Model, Entropy, Grey Incidence Analysis, Interval, Uncertainty

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Matthew J. Daskilewicz, Brian J. German, Timothy T. Takahashi, Shane Donovan, Arvin Shajanian. Effects of Disciplinary Uncertainty on Multi-objective Optimization in Aircraft Conceptual Design[J], Structure Multidisciplinary Optimization, 2011, 44: 831–846.

DOI: 10.1007/s00158-011-0673-4

Google Scholar

[2] Satty T L. The Analytic Hierarchy Process [M]. New York: McGraw-Hill, (1980).

Google Scholar

[3] Hwang C L, Yoon K S. Multiple Attribute Decision Making [M]. Berlin: Springer, (1981).

Google Scholar

[4] CHEN Ting. Decision Analysis. BEI JING: Scientific press, 1987. (in Chinese).

Google Scholar

[5] XU S B. theory of analytical hierarchy process. TIAN JIN：University of Tianjin press, 1988. (in Chinese).

Google Scholar