An Optimal Composition Strategy for Knowledge Service Component Based on Flexible Tracking Particle Swarm Algorithm
It is urgent to combine knowledge resources with manufacturing business processes to form a knowledge service in the cloud mode, so as to provide intelligent support for business activities in product development process. The main challenge of knowledge resource service, however, is how to rapidly c...
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2019/8545364 |
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| author | Yan-chao Yin Fu-zhao Chen Wei-zhi Liao Cui-yin Liu |
| author_facet | Yan-chao Yin Fu-zhao Chen Wei-zhi Liao Cui-yin Liu |
| author_sort | Yan-chao Yin |
| collection | DOAJ |
| description | It is urgent to combine knowledge resources with manufacturing business processes to form a knowledge service in the cloud mode, so as to provide intelligent support for business activities in product development process. The main challenge of knowledge resource service, however, is how to rapidly construct the complex resource service system and respond promptly to the changeable service requirements in the business process, which is similar to the software system modeling using a component in software engineering. This paper is concerned with an optimal composition framework (OCF) of knowledge resource service, including service decomposition, component encapsulation, and optimal composition. Firstly, the typical business processes are decomposed into the dynamic knowledge element (DKE), and all kinds of knowledge resources and service behaviors are encapsulated into the reusable resource service components (RSC). Then, a multicomponent optimal composition mathematical model is presented, which transforms the problem of component composition into a multiobjective optimization problem. On this basis, a heuristic algorithm with the adaptive mutation probability is introduced to composite the multigranularity service component dynamically and robustly. Finally, the case of component composition for maintenance resource service is studied and the simulation results are provided to verify the efficacy of the proposed model and algorithms. |
| format | Article |
| id | doaj-art-4fe2a2f183cf46b7953e9e6cc6c9718e |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-4fe2a2f183cf46b7953e9e6cc6c9718e2025-02-03T01:12:27ZengWileyComplexity1076-27871099-05262019-01-01201910.1155/2019/85453648545364An Optimal Composition Strategy for Knowledge Service Component Based on Flexible Tracking Particle Swarm AlgorithmYan-chao Yin0Fu-zhao Chen1Wei-zhi Liao2Cui-yin Liu3Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming, ChinaFaculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming, ChinaSchool of Mechanical and Electrical Engineering, University of Electronic Science and Technology, Chengdu, ChinaYunnan Province Key Laboratory of Computer Technology Applications, Kunming University of Science and Technology, Kunming, ChinaIt is urgent to combine knowledge resources with manufacturing business processes to form a knowledge service in the cloud mode, so as to provide intelligent support for business activities in product development process. The main challenge of knowledge resource service, however, is how to rapidly construct the complex resource service system and respond promptly to the changeable service requirements in the business process, which is similar to the software system modeling using a component in software engineering. This paper is concerned with an optimal composition framework (OCF) of knowledge resource service, including service decomposition, component encapsulation, and optimal composition. Firstly, the typical business processes are decomposed into the dynamic knowledge element (DKE), and all kinds of knowledge resources and service behaviors are encapsulated into the reusable resource service components (RSC). Then, a multicomponent optimal composition mathematical model is presented, which transforms the problem of component composition into a multiobjective optimization problem. On this basis, a heuristic algorithm with the adaptive mutation probability is introduced to composite the multigranularity service component dynamically and robustly. Finally, the case of component composition for maintenance resource service is studied and the simulation results are provided to verify the efficacy of the proposed model and algorithms.http://dx.doi.org/10.1155/2019/8545364 |
| spellingShingle | Yan-chao Yin Fu-zhao Chen Wei-zhi Liao Cui-yin Liu An Optimal Composition Strategy for Knowledge Service Component Based on Flexible Tracking Particle Swarm Algorithm Complexity |
| title | An Optimal Composition Strategy for Knowledge Service Component Based on Flexible Tracking Particle Swarm Algorithm |
| title_full | An Optimal Composition Strategy for Knowledge Service Component Based on Flexible Tracking Particle Swarm Algorithm |
| title_fullStr | An Optimal Composition Strategy for Knowledge Service Component Based on Flexible Tracking Particle Swarm Algorithm |
| title_full_unstemmed | An Optimal Composition Strategy for Knowledge Service Component Based on Flexible Tracking Particle Swarm Algorithm |
| title_short | An Optimal Composition Strategy for Knowledge Service Component Based on Flexible Tracking Particle Swarm Algorithm |
| title_sort | optimal composition strategy for knowledge service component based on flexible tracking particle swarm algorithm |
| url | http://dx.doi.org/10.1155/2019/8545364 |
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