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Is our mission profitable: The cost-effectiveness curve with a possibility of a mission abort

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  • Finkelstein, Maxim
  • Cha, Ji Hwan

Abstract

We consider missions of fixed and random duration and are interested in their cost-effectiveness at each instant of time. As a measure of quality, the difference between the expected conditional profit (on condition that a system is operable at the current time) and a profit already earned up to this time in case of a mission abort is suggested. This takes into account the corresponding penalties and rewards due to abort or completion of a mission, respectively. However, the main focus is on cost-effective missions and requirements for achieving it. As a result, the cost effectiveness curve is obtained for two cases: with and without observing a univariate degradation process of a system. Specifically, when the degradation is observable, the cost effectiveness curve (at each instant of a mission time) indicates the value of degradation on exceeding which, a mission becomes non-profitable with respect to the suggested criterion. The detailed numerical examples illustrate our findings.

Suggested Citation

  • Finkelstein, Maxim & Cha, Ji Hwan, 2025. "Is our mission profitable: The cost-effectiveness curve with a possibility of a mission abort," Reliability Engineering and System Safety, Elsevier, vol. 257(PA).
    • Handle: RePEc:eee:reensy:v:257:y:2025:i:pa:s0951832025000560
    DOI: 10.1016/j.ress.2025.110853
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    References listed on IDEAS

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    1. Cha, Ji Hwan & Finkelstein, Maxim & Levitin, Gregory, 2018. "Optimal mission abort policy for partially repairable heterogeneous systems," European Journal of Operational Research, Elsevier, vol. 271(3), pages 818-825.
    2. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2023. "Optimal aborting policy for shock exposed missions with random rescue time," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    3. Qiu, Qingan & Cui, Lirong, 2019. "Gamma process based optimal mission abort policy," Reliability Engineering and System Safety, Elsevier, vol. 190(C), pages 1-1.
    4. Maxim Finkelstein & Gregory Levitin, 2018. "Optimal Mission Duration for Partially Repairable Systems Operating in a Random Environment," Methodology and Computing in Applied Probability, Springer, vol. 20(2), pages 505-516, June.
    5. Levitin, Gregory & Finkelstein, Maxim, 2018. "Optimal mission abort policy for systems in a random environment with variable shock rate," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 11-17.
    6. Zhao, Xian & Liu, Haoran & Wu, Yaguang & Qiu, Qingan, 2023. "Joint optimization of mission abort and system structure considering dynamic tasks," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    7. Gregory Levitin & Maxim Finkelstein, 2018. "Optimal Mission Abort Policy for Systems Operating in a Random Environment," Risk Analysis, John Wiley & Sons, vol. 38(4), pages 795-803, April.
    8. Liu, Lujie & Yang, Jun, 2023. "A dynamic mission abort policy for the swarm executing missions and its solution method by tailored deep reinforcement learning," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    9. Qiu, Qingan & Cui, Lirong, 2019. "Optimal mission abort policy for systems subject to random shocks based on virtual age process," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 11-20.
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    11. Cheng, Guoqing & Shen, Jiayi & Wang, Fang & Li, Ling & Yang, Nan, 2024. "Optimal mission abort policy for a multi-component system with failure interaction," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    12. Qiu, Qingan & Cui, Lirong & Wu, Bei, 2020. "Dynamic mission abort policy for systems operating in a controllable environment with self-healing mechanism," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
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