A Method of Semantic Web Service Automatic Composition Based on Genetic Algorithm

Lu, Mingxiang; Li, Haisheng; Cai, Qiang

doi:10.1007/978-3-642-29455-6_99

Cited by 7 publications

(3 citation statements)

References 4 publications

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“…Its advantages include parallel computing, group optimization, background knowledge independence, and so on. The commonly used algorithms include genetic algorithm (Lu et al, 2012;Hung and Dduan, 2010;Wang et al, 2009), ant colony algorithm (Fang et al, 2009;Li et al, 2010b), etc.…”

Section: Related Workmentioning

confidence: 99%

Autonomous evolution of service system in cluster supply chain

2015

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Purpose – The purpose of this paper is to provide strong theoretical and technical support for the dynamic evolution of service system in “Cluster Supply Chain”(CSC), which can deal with two kinds of context changes: the internal service component changes and the external customer requirement changes. Design/methodology/approach – A “feedback-based” evolution mechanism of service system for CSC is proposed in this study. By means of the feedback update of enterprise service’s Quality of Service (QoS) attribute and the adjustment of the assumed QoS evaluation model, the evolution of service system can be achieved to suit the dynamic market demands. Findings – Results of the study suggest: by means of the “feed-back” evolution mechanism of service system, the enterprises in CSC can handle the context changes effectively to maintain the optimized operation status. Practical implications – The implementation of evolution mechanism in service system can keep the effectiveness of enterprise service composition to face the frequent service component changes and the unpredictable market turbulence. Originality/value – This paper proposes a method to realize the autonomous evolution of service system in CSC, which can support the flexibility and adaptability of enterprise service composition in the changing environment.

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Section: Related Workmentioning

confidence: 99%

Autonomous evolution of service system in cluster supply chain

2015

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“…As the number of available web services is rapidly increasing, service discovery and composition become two of most important research topics for both industry and academia since they can satisfy users' diverse requirements . Response time is an important factor of Quality of Service (QoS).…”

Section: Introductionmentioning

confidence: 99%

Performance formula‐based optimal deployments of multilevel indices for service retrieval

Liu

et al. 2017

Concurrency and Computation

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Summary There are many different index structures for service repositories, such as sequential index, inverted index, and multilevel indices that include three deployments. Different service sets maybe have different characteristics that may affect performance from different aspects. For a given service set, which index structure is the most optimal one? To address these issues, this paper analyses five indexing models and proposes expectation of traversed service count to estimate performance of service retrieval. Based on these expectation formulas, an optimal deployment method can be identified to maximize efficiency of service retrieval. Our experiments first validate correctness of the proposed formulas and then validate the effective of the optimal method.

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“…(3) Genetic Algorithm [3] (Genetic Algorithm, GA): it is a kind of effective random search algorithms simulating evolutionary process, and through delivery mechanisms such as natural selection, cross and mutation, it can improve the adaptive ability of the individual. Genetic Java software development engineer…”

Section: Introductionsmentioning

confidence: 99%

Research and Implementation of Professional Quality of Personnel Evaluation System Based on Multi-Dimensional

Jiang

2014

AMM

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this paper uses a new genetic algorithm (New Genetic Algorithm, NGA) to implement the automatic group volume function, solving the problem that the paper is not fully considered scores distribution of knowledge points in the test paper (test dimension) in the system using traditional genetic algorithm (Genetic Algorithm, GA) to implement automatic group volume, putting forward and redefining the fitness function to speed up the convergence. Simulation experiments show that the NGA algorithm is not only efficient, but can generate a valid paper, making the paper score can on the multi-dimensional of the test as far as possible to achieve uniform distribution.

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A Method of Semantic Web Service Automatic Composition Based on Genetic Algorithm

Cited by 7 publications

References 4 publications

Autonomous evolution of service system in cluster supply chain

Autonomous evolution of service system in cluster supply chain

Performance formula‐based optimal deployments of multilevel indices for service retrieval

Research and Implementation of Professional Quality of Personnel Evaluation System Based on Multi-Dimensional

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