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An Optimal Composition Strategy for Knowledge Service Component Based on Flexible Tracking Particle Swarm Algorithm

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  • Yan-chao Yin
  • Fu-zhao Chen
  • Wei-zhi Liao
  • Cui-yin Liu

Abstract

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.

Suggested Citation

  • Yan-chao Yin & Fu-zhao Chen & Wei-zhi Liao & Cui-yin Liu, 2019. "An Optimal Composition Strategy for Knowledge Service Component Based on Flexible Tracking Particle Swarm Algorithm," Complexity, Hindawi, vol. 2019, pages 1-14, December.
    • Handle: RePEc:hin:complx:8545364
    DOI: 10.1155/2019/8545364
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    References listed on IDEAS

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    1. Vendrell-Herrero, Ferran & Gomes, Emanuel & Bustinza, Oscar F. & Mellahi, Kamel, 2018. "Uncovering the role of cross-border strategic alliances and expertise decision centralization in enhancing product-service innovation in MMNEs," International Business Review, Elsevier, vol. 27(4), pages 814-825.
    2. Jorick Lartigau & Xiaofei Xu & Lanshun Nie & Dechen Zhan, 2015. "Cloud manufacturing service composition based on QoS with geo-perspective transportation using an improved Artificial Bee Colony optimisation algorithm," International Journal of Production Research, Taylor & Francis Journals, vol. 53(14), pages 4380-4404, July.
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