Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies
Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies
Towards Heuristic Web Services Composition Using Immune Algorithm
ICWS '08 Proceedings of the 2008 IEEE International Conference on Web Services
Optimal Web Service Selection based on Multi-Objective Genetic Algorithm
ISCID '08 Proceedings of the 2008 International Symposium on Computational Intelligence and Design - Volume 01
Optimizing QoS-Aware Semantic Web Service Composition
ISWC '09 Proceedings of the 8th International Semantic Web Conference
Firefly algorithms for multimodal optimization
SAGA'09 Proceedings of the 5th international conference on Stochastic algorithms: foundations and applications
Immune-inspired method for selecting the optimal solution in web service composition
RED'09 Proceedings of the 2nd international conference on Resource discovery
QoS-Based Dynamic Web Service Composition with Ant Colony Optimization
COMPSAC '10 Proceedings of the 2010 IEEE 34th Annual Computer Software and Applications Conference
IEEE Computational Intelligence Magazine
Bio-inspired computation: success and challenges of IJBIC
International Journal of Bio-Inspired Computation
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This paper presents two bio-inspired methods one inspired by the cuckoo's breeding behaviour, and another one inspired by natural evolution and genetics for selecting the optimal or near-optimal solution in web service composition. The proposed methods are applied on an enhanced planning graph structure which models the composition search space for a given user request. The cuckoo-inspired selection method applies a 1-OPT heuristic to expand the search space in a controlled way such that the stagnation in a local optimum solution is avoided. The genetic-based selection method uses two memory structures to avoid the stagnation in a local optimum solution on one hand, and to ensure that exploitation and exploration are properly performed. The quality of a composition solution is evaluated in terms of QoS attributes and semantic quality. To validate the proposed methods we have implemented an experimental prototype and carried out experiments on a set of scenarios with different complexities. Finally, we comparatively analyse the experimental results obtained by applying the two selection methods.