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    Deterministic conversion of uncertain manpower planning optimization problem

    264336.pdf (3.220Mb)
    Access Status
    Open access
    Authors
    Li, B.
    Zhu, Y.
    Sun, Y.
    Grace, A.
    Teo, Kok Lay
    Date
    2018
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Li, B. and Zhu, Y. and Sun, Y. and Grace, A. and Teo, K.L. 2018. Deterministic conversion of uncertain manpower planning optimization problem. IEEE Transactions on Fuzzy Systems. 26 (5): pp. 2748 - 2757.
    Source Title
    IEEE Transactions on Fuzzy Systems
    DOI
    10.1109/TFUZZ.2018.2803736
    ISSN
    1063-6706
    School
    School of Electrical Engineering, Computing and Mathematical Science (EECMS)
    Remarks

    © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

    URI
    http://hdl.handle.net/20.500.11937/66534
    Collection
    • Curtin Research Publications
    Abstract

    Manpower planning is a very important component of human resource management. However, there are many indeterminate factors that should be taken into consideration in manpower planning. For example, the decision of employees to quit the job is determined by their preference, which is beyond the control of human resource department. It can be realistically modeled as a random variable when the historical data of quitting rate is large enough. Otherwise, it can only be regarded as an uncertain variable when the historical data is inadequate. In this paper, we discuss a manpower planning optimization problem for a manufacturing company with hierarchical system, where the quitting rate of employees is modeled as an uncertain variable. First, we formulate a mathematical model for this uncertain manpower planning optimization problem, where the influence on the production outputs by employees is taken into consideration. Second, we present a deterministic conversion method to transform this uncertain manpower planning optimization problem into an equivalent deterministic discrete-time optimization problem. It is further converted into an equivalent linear programming model with an equality constraint and an inequality constraint. Finally, we use the real data from Singapore, Denmark and China to carry out a numerical simulation and make a comparison with the results obtained based on stochastic model to show the advantages of our method.

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