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A New Manufacturing Service Selection and Composition Method Using Improved Flower Pollination Algorithm

Author

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  • Wenyu Zhang
  • Yushu Yang
  • Shuai Zhang
  • Dejian Yu
  • Yangbing Xu

Abstract

With an increasing number of manufacturing services, the means by which to select and compose these manufacturing services have become a challenging problem. It can be regarded as a multiobjective optimization problem that involves a variety of conflicting quality of service (QoS) attributes. In this study, a multiobjective optimization model of manufacturing service composition is presented that is based on QoS and an environmental index. Next, the skyline operator is applied to reduce the solution space. And then a new method called improved Flower Pollination Algorithm (FPA) is proposed for solving the problem of manufacturing service selection and composition. The improved FPA enhances the performance of basic FPA by combining the latter with crossover and mutation operators of the Differential Evolution (DE) algorithm. Finally, a case study is conducted to compare the proposed method with other evolutionary algorithms, including the Genetic Algorithm, DE, basic FPA, and extended FPA. The experimental results reveal that the proposed method performs best at solving the problem of manufacturing service selection and composition.

Suggested Citation

  • Wenyu Zhang & Yushu Yang & Shuai Zhang & Dejian Yu & Yangbing Xu, 2016. "A New Manufacturing Service Selection and Composition Method Using Improved Flower Pollination Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-12, December.
    • Handle: RePEc:hin:jnlmpe:7343794
    DOI: 10.1155/2016/7343794
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    Cited by:

    1. Yong Chen & Zhengjie Wu & Wenchao Yi & Bingjia Wang & Jianhua Yao & Zhi Pei & Jiaoliao Chen, 2022. "Bibliometric Method for Manufacturing Servitization: A Review and Future Research Directions," Sustainability, MDPI, vol. 14(14), pages 1-26, July.

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