An approach for QoS-aware service composition based on genetic algorithms
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Muiltiobjective optimization using nondominated sorting in genetic algorithms
Evolutionary Computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Equitable solutions in QoS-aware service optimization
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Adaptive MOEA/D for QoS-based web service composition
EvoCOP'13 Proceedings of the 13th European conference on Evolutionary Computation in Combinatorial Optimization
A traffic shaping optimization methodology for web systems
Proceedings of the 19th Brazilian symposium on Multimedia and the web
Information and Software Technology
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Web services are rapidly changing the landscape of software engineering. One of the most important technologies introduced by them is Web service composition (WSC). In this paper, we model the Quality of Service (QoS)-aware service composition problem as a multiobjective optimization problem (MOP). A corresponding algorithm that based on Nondominated Sorting Genetic Algorithm-II (NSGA-II) is proposed to solve the problem. The algorithm generates a set of Pereto optimal solutions which satisfy users' requirement. Our experimental results show that by using the proposed algorithm, we can give service consumers several different feasible solutions which make decision easier.