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Optimizing location of manufacturing industries in the context of economic globalization: A bi-level model based approach

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  • Wu, Shanhua
  • Yang, Zhongzhen

Abstract

This paper aims to optimize the locations of manufacturing industries in the context of economic globalization by proposing a bi-level programming model which integrates the location optimization model with the traffic assignment model. In the model, the transport network is divided into the subnetworks of raw materials and products respectively. The upper-level model is used to determine the location of industries and the OD matrices of raw materials and products. The lower-level model is used to calculate the attributes of traffic flow under given OD matrices. To solve the model, the genetic algorithm is designed. The proposed method is tested using the Chinese steel industry as an example. The result indicates that the proposed method could help the decision-makers to implement the location decisions for the manufacturing industries effectively.

Suggested Citation

  • Wu, Shanhua & Yang, Zhongzhen, 2018. "Optimizing location of manufacturing industries in the context of economic globalization: A bi-level model based approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 327-337.
    • Handle: RePEc:eee:phsmap:v:501:y:2018:i:c:p:327-337
    DOI: 10.1016/j.physa.2018.02.042
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    Cited by:

    1. Chenxi Li & Kening Wu, 2022. "An input–output analysis of transportation equipment manufacturing industrial transfer: Evidence from Beijing‐Tianjin‐Hebei region, China," Growth and Change, Wiley Blackwell, vol. 53(1), pages 91-111, March.
    2. Yang, Yun & Ma, Changxi & Ling, Gang, 2022. "Pre-location for temporary distribution station of urban emergency materials considering priority under COVID-19: A case study of Wuhan City, China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 597(C).
    3. Zhang, Hao & Wang, Mingyue & Cheng, Zhixuan & Wan, Ling, 2020. "Technology-sharing strategy and incentive mechanism for R&D teams of manufacturing enterprises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).

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