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Joint optimization of the high-end equipment development task process and resource allocation

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Abstract

Considering the various uncertainties in the implementation process of high-end equipment development tasks, the Monte Carlo simulation method is used to simulate the execution process of these tasks. Parameters such as the average duration and cost of the simulation output are used to evaluate the fitness of individuals, and consequently, the development process is optimized using the NSGA-III algorithm. By comparing the optimization results of the development task process under different quantities of resources, the impact of the quantity of resources on the optimization results of the development task process is analyzed. With a view to obtain a more satisfactory development task process, the PSO algorithm is nested into NSGA-III. The Pareto front solution set is obtained from the optimization of the task process. The PSO algorithm is applied to optimize the resource allocation for the development task process. Joint optimization of the high-end equipment development task process and resource allocation is carried out. Finally, the effectiveness of the proposed method is verified by an example.

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Acknowledgements

The authors would like to thank the anonymous referees for the valuable comments and suggestions which help us to improve this paper. This work was supported by the National Natural Science Foundation (NSF) of China (No. 71690233) and National Key R&D Program of China under Grant nos. SQ2017YFSF070185.

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Authors and Affiliations

  1. College of Systems Engineering, National University of Defense Technology, Changsha, 410073, China

    Xilin Zhang, Yuejin Tan & Zhiwei Yang

  2. Business School, Jiangsu Normal University, Xuzhou, 221116, China

    Xilin Zhang

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  1. Xilin Zhang
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  2. Yuejin Tan
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  3. Zhiwei Yang
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Correspondence to Zhiwei Yang.

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Zhang, X., Tan, Y. & Yang, Z. Joint optimization of the high-end equipment development task process and resource allocation. Nat Comput 19, 811–823 (2020). https://doi.org/10.1007/s11047-018-9722-x

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  • DOI: https://doi.org/10.1007/s11047-018-9722-x

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