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Research on extremely short construction period of engineering project based on labor balance under resource tolerance

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  • Junlong Peng
  • Mengyao Wang
  • Chao Peng
  • Ke Hu

Abstract

Under the condition of resource tolerance, engineering construction projects face the problem of labor force balance in the working face. Notably, a deviation occurs between the distribution and certain demand of the labor force in the limited working face, which affects the realization of an extremely short construction period. To address this problem, we first introduced the stochastic coefficient of labor force equilibrium to measure the degree of labor balance. Second, a labor force equilibrium model with the realization goal of an extremely short construction period was established. Then, the standard particle swarm optimization (PSO) algorithm was improved from two perspectives to solve the proposed model. The update equation was rounded to solve practical project problems, and a dynamic variable inertia weight was adopted to ensure the PSO algorithm accuracy and convergence speed. Finally, through case analysis, we determined the extremely short construction period and best labor force distribution scheme. Moreover, the case results revealed that the established model is simple, operable and practical and that the proposed algorithm achieves a high search accuracy and efficiency in the model solution process. Overall, under the condition of resource tolerance, this study provides scientific and effective references for managers to realize an extremely short construction period.

Suggested Citation

  • Junlong Peng & Mengyao Wang & Chao Peng & Ke Hu, 2022. "Research on extremely short construction period of engineering project based on labor balance under resource tolerance," PLOS ONE, Public Library of Science, vol. 17(3), pages 1-18, March.
  • Handle: RePEc:plo:pone00:0266036
    DOI: 10.1371/journal.pone.0266036
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    References listed on IDEAS

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    1. Basem Al Khatib & Yap Soon Poh & Ahmed El-Shafie, 2020. "Delay Factors Management and Ranking for Reconstruction and Rehabilitation Projects Based on the Relative Importance Index (RII)," Sustainability, MDPI, vol. 12(15), pages 1-21, July.
    2. Gonçalves, J.F. & Mendes, J.J.M. & Resende, M.G.C., 2008. "A genetic algorithm for the resource constrained multi-project scheduling problem," European Journal of Operational Research, Elsevier, vol. 189(3), pages 1171-1190, September.
    3. Kolisch, Rainer & Hartmann, Sonke, 2006. "Experimental investigation of heuristics for resource-constrained project scheduling: An update," European Journal of Operational Research, Elsevier, vol. 174(1), pages 23-37, October.
    4. M. Suresh & Pankaj Dutta & Karuna Jain, 2015. "Resource Constrained Multi-Project Scheduling Problem with Resource Transfer Times," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 32(06), pages 1-30, December.
    5. Guangquan Lu & Ying Xiong & Chuan Ding & Yunpeng Wang, 2016. "An Optimal Schedule for Urban Road Network Repair Based on the Greedy Algorithm," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-15, October.
    6. Pellerin, Robert & Perrier, Nathalie & Berthaut, François, 2020. "A survey of hybrid metaheuristics for the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 280(2), pages 395-416.
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