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Human resource allocation for multiple scientific research projects via improved pigeon-inspired optimization algorithm

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Abstract

Aiming at the complex and restrictive characteristics of human resource allocation in multiple scientific university research projects, an improved pigeon-inspired optimization (IPIO) algorithm is proposed wherein loss minimization and the shortest project delay time are considered as optimization goals. Firstly, mathematical modelling of the problem is carried out, and the multi-objective optimization problem is transformed into a single-objective optimization problem by means of a weighted solution. In the second step, the traditional pigeon-inspired optimization (PIO) algorithm is discretized, and an adaptive parameter strategy is adopted to improve the shortcomings of the algorithm itself. Finally, by comparing the simulation results with the original algorithm and the genetic algorithm in the optimization of human resource allocation in multiple projects, the feasibility and superiority of the proposed algorithm in the optimization of human resource allocation in multi-scientific research projects is verified.

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Authors and Affiliations

  1. School of Economics and Management, Harbin Engineering University, Harbin, 150001, China

    ChuanBin Liu, YongHong Ma, Hang Yin & LeAn Yu

  2. Science and Technology Development Center, Ministry of Education, Beijing, 100080, China

    ChuanBin Liu

Authors
  1. ChuanBin Liu
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  2. YongHong Ma
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  3. Hang Yin
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  4. LeAn Yu
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Corresponding authors

Correspondence to ChuanBin Liu or LeAn Yu.

Additional information

This work was supported by the Fundamental Research Funds for the Central Scientific Research Institutes (Grant No. 20200306).

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Liu, C., Ma, Y., Yin, H. et al. Human resource allocation for multiple scientific research projects via improved pigeon-inspired optimization algorithm. Sci. China Technol. Sci. 64, 139–147 (2021). https://doi.org/10.1007/s11431-020-1577-0

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  • DOI: https://doi.org/10.1007/s11431-020-1577-0

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