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A two-stage intervened decision system with multi-state decision units and dynamic system configuration

Author

Listed:
  • Tingnan Lin

    (Rutgers University)

  • Hoang Pham

    (Rutgers University)

Abstract

This paper develops the performability and cost–benefit models for a two-stage intervened decision system with majority voting rule and binary input and output. The decision process of the system contains two stages: an inspection stage (stage 1) and a result submission stage (stage 2). During the first stage, each decision unit in the system will have multiple states and a supervisor will come to visit each unit and check its state for at most twice. The supervisor will conduct the first visit to each unit for certain. However, the behavior of the second visit to each unit will be determined by its state during the first visit. In addition, each decision unit may be removed from the system given certain states during each visit. Therefore the structure of system may change during the decision process. The units which are not removed during the first stage can submit the result at any time during the second stage. However, the performance of each remaining unit will be determined by the ending state of the first stage. Moreover, in order to improve the efficiency of the decision process, a check point is added to the second stage. The performability and cost–benefit models for this dynamic system are developed by considering the distribution of states at the end of the first stage. A three-step method will be proposed for model optimization. Some numerical examples for the three-step method will be presented. The proposed intervened decision system in this paper can be applied in many contexts such as financial investment, paper submission review and proposal evaluation, credit evaluation and loan application and product release and recall.

Suggested Citation

  • Tingnan Lin & Hoang Pham, 2022. "A two-stage intervened decision system with multi-state decision units and dynamic system configuration," Annals of Operations Research, Springer, vol. 311(1), pages 255-277, April.
    • Handle: RePEc:spr:annopr:v:311:y:2022:i:1:d:10.1007_s10479-019-03334-8
    DOI: 10.1007/s10479-019-03334-8
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    References listed on IDEAS

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