CSAA: A Constraint Satisfaction Ant Algorithm Framework

2004 ◽  
pp. 285-294 ◽  
Author(s):  
Koenraad Mertens ◽  
Tom Holvoet
Keyword(s):  
Constraint Satisfaction ◽  
Ant Algorithm ◽  
Algorithm Framework

scholarly journals Sandwiches for promise constraint satisfaction

2021 ◽  
Vol 82 (1) ◽  
Author(s):  
Guofeng Deng ◽  
Ezzeddine El Sai ◽  
Trevor Manders ◽  
Peter Mayr ◽  
Poramate Nakkirt ◽  
...  
Keyword(s):  
Constraint Satisfaction

A complementary webometric ranking system based on the website quality and traffic measures: A study focusing on top-ranked world universities

2021 ◽  
pp. 1-18
Author(s):  
Sajjad Farashi ◽  
Saeed Bashirian
Keyword(s):  
Weight Vector ◽  
Quality Factors ◽  
Ranking System ◽  
Web Based ◽  
Website Quality ◽  
Scientific Advancement ◽  
Standard Models ◽  
Algorithm Framework ◽  
Scientific Results ◽  
Optimal Weight Vector

Ranking of universities regarding their web-based activities plays a pivotal role in promoting scientific advancement since it motivates the open access accessibility to scientific results. In this study, a new ranking system based on the website quality factors and traffic evaluation was proposed. Since top-ranked universities are usually considered as the standard models for lower ranked ones, the focus of this study was on top-ranked universities. The proposed ranking was compared with well-known Webometrics ranking system. The website traffic and quality assessment were acquired for websites of top-ranked world universities and the correlation between these indices and the Webometrics ranking was evaluated. The summation of the weighted value of obtained measures according to an optimal weight vector obtained by a genetic algorithm framework was used for ranking purposes. The results showed that the website total traffic size was correlated with Webometrics rank (R≈-0.6, p< 0.01). Also, using the weighted value of website quality and traffic measures, the proposed ranking system could predict Webometrics ranking by the accuracy of up to 69%. Even though the method was proposed for universities, it could be applied for ranking other types of centers or companies, provided that the suitable cost function for the genetics algorithm framework was defined.

Deep Stalling using a Coverage Driven Genetic Algorithm Framework

2021 ◽  
Author(s):  
Siddhanth Dhodhi ◽  
Debarshi Chatterjee ◽  
Eric Hill ◽  
Saad Godil
Keyword(s):  
Genetic Algorithm ◽  
Algorithm Framework
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