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A Hybrid Parallel Processing Strategy for Large-Scale DEA Computation

Author

Listed:
  • Shengqing Chang

    (Hefei University of Technology)

  • Jingjing Ding

    (Hefei University of Technology
    Intelligent Interconnection System Anhui Provincial Laboratory
    (Hefei University of Technology), Ministry of Education)

  • Chenpeng Feng

    (Hefei University of Technology
    Intelligent Interconnection System Anhui Provincial Laboratory
    (Hefei University of Technology), Ministry of Education)

  • Ruifeng Wang

    (SPD Bank)

Abstract

Using data envelopment analysis (DEA) with large-scale data poses a big challenge to applications due to its computing-intensive nature. So far, various strategies have been proposed in academia to accelerate the DEA computation, including DEA algorithms such as hierarchical decomposition (HD), DEA enhancements such as restricted basis entry (RBE) and LP accelerators such as hot starts. However, few studies have integrated these strategies and combined them with a parallel processing framework to solve large-scale DEA problems. In this paper, a hybrid parallel DEA algorithm (named PRHH algorithm) is proposed, including the RBE algorithm, hot starts, and HD algorithm based on Message Passing Interface (MPI). Furthermore, the attribute of the PRHH algorithm is analyzed, and formalized as a computing time function, to shed light on its time complexity. Finally, the performance of the algorithm is investigated in various simulation scenarios with datasets of different characteristics and compared with existing methods. The results show that the proposed algorithm reduces computing time in general, and boosts performance dramatically in scenarios with low density in particular.

Suggested Citation

  • Shengqing Chang & Jingjing Ding & Chenpeng Feng & Ruifeng Wang, 2024. "A Hybrid Parallel Processing Strategy for Large-Scale DEA Computation," Computational Economics, Springer;Society for Computational Economics, vol. 63(6), pages 2325-2349, June.
    • Handle: RePEc:kap:compec:v:63:y:2024:i:6:d:10.1007_s10614-023-10407-1
    DOI: 10.1007/s10614-023-10407-1
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    References listed on IDEAS

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