Paper Info
Title
Fuzzy-Guided Genetic Algorithm Applied To The Web Service Selection Problem
Abstract
The benefits of Quality of Service (QoS) aware service selection is undisputed. The selection process based on QoS allows the user to specify their requirements not only based on functional attributes but also on non-functional attributes. The automation of this selection process can be done via optimization. Several different exact but also approximate algorithms have been proposed in the past. Genetic algorithm is one such method that can find approximate solutions during the service selection task. In this paper, we propose an improved version of the standard genetic algorithm approach by making use of fuzzy logic during the stochastic genetic search process. The fuzzy component dynamically adjusts the crossover and mutation rates of the evolution for every ten consecutive generations. Results show that the fuzzy-guided Genetic algorithm approach improves the solution quality.
Year
DOI
Venue
2012
10.1109/FUZZ-IEEE.2012.6251248
2012 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE)
Keywords
Field
DocType
optimization,quality of service,fuzzy logic,genetic algorithms,reliability,qos,mutation rates,web services,fuzzy set theory
Data mining,Crossover,Computer science,Fuzzy logic,Quality of service,Fuzzy set,Automation,Artificial intelligence,Web service,Quality control and genetic algorithms,Machine learning,Genetic algorithm
Conference
ISSN
Citations 
PageRank 
1098-7584
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Min Chen1162.06
Simone A Ludwig21309179.41