A multi-attribute decision-making approach to the selection of point-of-use water treatment

2015 ◽  
Vol 35 (4) ◽  
pp. 437-452 ◽  
Author(s):  
Sheree A. Pagsuyoin ◽  
Joost R. Santos ◽  
Jana S. Latayan ◽  
John R. Barajas
Keyword(s):  
Decision Making ◽  
Water Treatment ◽  
Point Of Use ◽  
Multi Attribute Decision Making ◽  
Selection Of

Thermo-chemical water splitting: Selection of priority reversible redox reactions by multi-attribute decision making

2021 ◽  
Vol 170 ◽  
pp. 800-810
Author(s):  
Yimin Deng ◽  
Raf Dewil ◽  
Lise Appels ◽  
Shuo Li ◽  
Jan Baeyens ◽  
...  
Keyword(s):  
Decision Making ◽  
Water Splitting ◽  
Redox Reactions ◽  
Reversible Redox ◽  
Multi Attribute Decision Making ◽  
Chemical Water ◽  
Selection Of

Location selection of seawater pumped hydro storage station in China based on multi-attribute decision making

2019 ◽  
Vol 139 ◽  
pp. 410-425 ◽  
Author(s):  
Yunna Wu ◽  
Ting Zhang ◽  
Chuanbo Xu ◽  
Xiaoyu Zhang ◽  
Yiming Ke ◽  
...  
Keyword(s):  
Decision Making ◽  
Location Selection ◽  
Storage Station ◽  
Multi Attribute Decision Making ◽  
Selection Of

scholarly journals A multi attribute decision making method for selection of optimal assembly line

2011 ◽  
Vol 1 (1) ◽  
pp. 65-72 ◽  
Author(s):  
B. Vijaya Ramnath ◽  
C. Elanchezhian ◽  
R. Kesavan
Keyword(s):  
Decision Making ◽  
Assembly Line ◽  
Multi Attribute Decision Making ◽  
Optimal Assembly ◽  
Selection Of

X-Abilities and Attributes Based Decision Making in Evaluation and Selection of a Turbine Blade Material

2014 ◽  
Author(s):  
Phaneendra Kiran Chaganti ◽  
Shibu Clement
Keyword(s):  
Decision Making ◽  
Turbine Blade ◽  
Conceptual Design ◽  
Concurrent Engineering ◽  
Design Stage ◽  
Engineering Approach ◽  
Design And Manufacturing ◽  
Multi Attribute Decision Making ◽  
The Given ◽  
Selection Of

The evaluation and selection of a turbine blade material involves several x-abilities and attributes. A designer should consider lifecycle issues as well as design and manufacturing strategies simultaneously at conceptual design stage without missing any of the information. In the proposed methodology the comparison is made between different turbine blade materials based on different x-abilities and attributes. The proposed methodology compares the materials using concurrent engineering approach and multi attribute decision making approach (MADM). In the concurrent engineering approach four x-abilities namely quality, manufacturing, environment and cost are considered. To maintain uniformity attributes considered in MADM approach are same as concurrent engineering approach. Both the methodologies show that ST12TE is the best material for turbine blade for the given set of attributes and x-abilities.

Location selection for Installation of Surface Water Treatment Plant by Applying a New Sinusoidal Analytical Hierarchy Process

2019 ◽  
Vol 8 (3) ◽  
pp. 20-42
Author(s):  
Sudipa Choudhury ◽  
Apu Kumar Saha
Keyword(s):  
Decision Making ◽  
Water Treatment ◽  
Surface Water ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Location Selection ◽  
Simulation And Optimization ◽  
Surface Water Treatment ◽  
Selection For ◽  
Selection Of

Water treatment plants (WTPs) are responsible for ensuring supply of healthy water to urban and rural consumers for drinking and other related purposes. But the arbitrary selection of a location for installation or relocation of WTPs often fails the purpose of the plant. Presently studies in location selection for water treatment plant are rare. Multi-criteria decision making (MCDM) methods and bagged polynomial neural networks (PNN) were found to be exemplary and easy to use tools for prediction, simulation and optimization of decision-making objectives. The present study tries to apply the advantages of MCDM and bagged PNNs in the identification of an ideal location for a surface water treatment plant. The most significant parameter is found to be WQI which represents the overall quality of water suitable for domestic use. The PNN models were developed with all the selected eight alternatives as input and output. The algorithms like GMDH, SFS, SMS, and QC were used to estimate the weight of connections in between the input and hidden; and hidden and output layers separately for each segment. The application of these two soft computation tools provides an opportunity to the decision maker in the selection of optimal location with the help of an objective and cognitive method.

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