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BSP‐GA: A new Genetic Algorithm for System Optimization and Excellent Schema Selection

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  • Chenxia Jin
  • Fachao Li
  • Marzana Wilamowska‐Korsak
  • Ling Li
  • Liuliu Fu

Abstract

The significance of Internet‐of‐Things to Supply Chain Management has been dramatically increasing. The performance of supply chain based on Internet‐of‐Things is largely dependent on its optimization. Genetic algorithms (GAs) are important intelligent methods for complex system optimization problems, but they have some internal drawbacks such as premature and slow convergence to the global optimum. In this paper, we present a new schema protection based GA (BSP‐GA). First, we propose three principles for selecting excellent schema based on the schema theory; second, we propose the concept of K‐intensive effect synthesis operator, and we give a general five‐intensive effect synthesis operator and its proof; third, we give the selection process of excellent schema through an example, and further we give the implementation steps of BSP‐GA. The performance of BSP‐GA has been compared with simple GA by using two carefully chosen benchmark problems. It has been observed that BSP‐GA can yield the global optimum more efficiently than commonly used simple GA. Furthermore, a theorem is presented to guarantee the convergence of BSP‐GA. Copyright © 2014 John Wiley & Sons, Ltd.

Suggested Citation

  • Chenxia Jin & Fachao Li & Marzana Wilamowska‐Korsak & Ling Li & Liuliu Fu, 2014. "BSP‐GA: A new Genetic Algorithm for System Optimization and Excellent Schema Selection," Systems Research and Behavioral Science, Wiley Blackwell, vol. 31(3), pages 337-352, May.
    • Handle: RePEc:bla:srbeha:v:31:y:2014:i:3:p:337-352
    DOI: 10.1002/sres.2280
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    References listed on IDEAS

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    1. Yiting Xing & Ling Li & Zhuming Bi & Marzena Wilamowska‐Korsak & Li Zhang, 2013. "Operations Research (OR) in Service Industries: A Comprehensive Review," Systems Research and Behavioral Science, Wiley Blackwell, vol. 30(3), pages 300-353, May.
    2. Chengen Wang & Lida Xu, 2008. "Parameter mapping and data transformation for engineering application integration," Information Systems Frontiers, Springer, vol. 10(5), pages 589-600, November.
    3. Li, Ling, 2013. "Technology designed to combat fakes in the global supply chain," Business Horizons, Elsevier, vol. 56(2), pages 167-177.
    4. Alberto Garcia-Villoria & Albert Corominas & Rafael Pastor, 2010. "Solving the response time variability problem by means of the cross-entropy method," International Journal of Manufacturing Technology and Management, Inderscience Enterprises Ltd, vol. 20(1/2/3/4), pages 316-330.
    5. García-Villoria, Alberto & Pastor, Rafael, 2010. "Solving the response time variability problem by means of a genetic algorithm," European Journal of Operational Research, Elsevier, vol. 202(2), pages 320-327, April.
    6. Li Da Xu, 2013. "Introduction: Systems Science in Industrial Sectors," Systems Research and Behavioral Science, Wiley Blackwell, vol. 30(3), pages 211-213, May.
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