Automated selection of optimal material for pressurized multi-layer composite tubes based on an evolutionary approach

2016 ◽  
Vol 29 (7) ◽  
pp. 405-416 ◽  
Author(s):  
Saeid Kazemzadeh Azad ◽  
Tolga Akış
Keyword(s):  
Evolutionary Approach ◽  
Composite Tubes ◽  
Layer Composite ◽  
Optimal Material ◽  
Selection Of

Research on Material Selection with Multi-Attribute Decision Method and G1 Method

2014 ◽  
Vol 952 ◽  
pp. 20-24 ◽  
Author(s):  
Xue Jun Xie
Keyword(s):  
Material Selection ◽  
Selection Process ◽  
Selection Problem ◽  
Topsis Method ◽  
Attribute Weight ◽  
Multi Attribute Decision Making ◽  
Judgment Matrix ◽  
Optimal Material ◽  
Selection Of ◽  
Better Than

The selection of an optimal material is an important aspect of design for mechanical, electrical, thermal, chemical or other application. Many factors (attributes) need to be considered in material selection process, and thus material selection problem is a multi-attribute decision making (MADM) problem. This paper proposes a new MADM method for material selection problem. G1 method does not need to test consistency of the judgment matrix. Thus it is better than AHP. In this paper, firstly, we use the G1 method to determine the attribute weight. Then TOPSIS method is used to calculate the closeness of the candidate materials with respect positive solution. A practical material selection case is used to demonstrate the effectiveness and feasibility of the proposed method.

scholarly journals Evolving Action Abstractions for Real-Time Planning in Extensive-Form Games

2019 ◽  
Vol 33 ◽  
pp. 2330-2337 ◽  
Author(s):  
Julian R. H. Mariño ◽  
Rubens O. Moraes ◽  
Claudio Toledo ◽  
Levi H. S. Lelis
Keyword(s):  
Real Time ◽  
Subset Selection ◽  
Evolutionary Approach ◽  
Planning Systems ◽  
Extensive Form ◽  
Player Game ◽  
Pure Strategies ◽  
Time Planning ◽  
Action Spaces ◽  
Selection Of

A key challenge for planning systems in real-time multiagent domains is to search in large action spaces to decide an agent’s next action. Previous works showed that handcrafted action abstractions allow planning systems to focus their search on a subset of promising actions. In this paper we show that the problem of generating action abstractions can be cast as a problem of selecting a subset of pure strategies from a pool of options. We model the selection of a subset of pure strategies as a two-player game in which the strategy set of the players is the powerset of the pool of options— we call this game the subset selection game. We then present an evolutionary algorithm for solving such a game. Empirical results on small matches of µRTS show that our evolutionary approach is able to converge to a Nash equilibrium for the subset selection game. Also, results on larger matches show that search algorithms using action abstractions derived by our evolutionary approach are able to substantially outperform all state-of-the-art planning systems tested.

Application of Distance Evaluation and its Improved Algorithms in Engineering Materials Selection

2007 ◽  
Vol 353-358 ◽  
pp. 2758-2761 ◽  
Author(s):  
T.Y. Zhang ◽  
Rui Chen Yang
Keyword(s):  
Low Temperature ◽  
Euclidean Distance ◽  
Materials Selection ◽  
Ahp Method ◽  
Storage Container ◽  
Low Temperature Storage ◽  
Engineering Materials ◽  
Optimal Material ◽  
Selection Of ◽  
Temperature Storage

Distance evaluation and its improved algorithms using Vertical distance instead of Euclidean distance were discussed in engineering materials selection. Taking the selection of materials for low temperature storage container as an example, based on eight kinds of evaluation indices, according to the weight obtained by AHP method, ten kinds of candidate materials were evaluated by using distance evaluation and its improved algorithms. The results indicate that, the optimal material selected coincides with the practice of industry, and the sequence of the candidate materials arranged using improved algorithms is more reliable, which shows that improved algorithms of distance evaluation is a feasible and effective way for engineering materials selection.

Neuro-evolutionary approach for optimal selection of EEG channels in motor imagery based BCI application

2021 ◽  
Vol 68 ◽  
pp. 102621
Author(s):  
Oluwagbenga Paul Idowu ◽  
Oluwaremilekun Adelopo ◽  
Ademola Enitan Ilesanmi ◽  
Xiangxin Li ◽  
Oluwarotimi Williams Samuel ◽  
...  
Keyword(s):  
Motor Imagery ◽  
Evolutionary Approach ◽  
Optimal Selection ◽  
Selection Of
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