Genetic algorithm-based multi-objective optimisation for QoS-aware web services composition

Authors:
Li Li;Pengyi Yang;Ling Ou;Zili Zhang;Peng Cheng
Affiliations:
Southwest University, Chongqing, P.R. China;School of IT, The University of Sydney, Sydney, Australia;Southwest University, Chongqing, P.R. China;Southwest University, Chongqing, P.R. China;Southwest University, Chongqing, P.R. China
Venue:
KSEM'10 Proceedings of the 4th international conference on Knowledge science, engineering and management
Year:
2010

Citing 5
Cited 0

Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization

Proceedings of the 5th International Conference on Genetic Algorithms
Adaptive Service Composition in Flexible Processes

IEEE Transactions on Software Engineering
Dynamic Web Service Selection for Reliable Web Service Composition

IEEE Transactions on Services Computing
An Agent-Based Hybrid System for Microarray Data Analysis

IEEE Intelligent Systems
A fast and elitist multiobjective genetic algorithm: NSGA-II

IEEE Transactions on Evolutionary Computation

Quantified Score

Hi-index	0.00

Visualization

Abstract

Finding an optimal solution for QoS-aware Web service composition with various restrictions on qualities is a multi-objective optimisation problem. A popular multi-objective genetic algorithm, NSGA-II, is studied in order to provide a set of optimal solutions for QoS-based service composition. Experiments with different numbers of abstract and concrete services confirm the expected behaviour of the algorithm.