A resilience-driven two-stage operational chain optimization model for unmanned weapon system-of-systems under limited resource environments

Enhancing the battlefield resilience of unmanned weapon system-of-systems (UWSoS) through structural reconstruction requires scheduling additional physical resources. However, they are scarce in limited resource environments. To address the challenge of resource constraints, this paper focuses on improving the resilience of UWSoS by optimizing the operational chain of tasks after a disruption. First, a task-oriented resilience metric is proposed to characterize the impact of operational chain variations on UWSoS resilience. Based on this, a two-stage operational chain optimization model for UWSoS under limited resource environments is established, which considers the optimization actions of the edge node and rear command node in different resilience phases after the interruption for resilience enhancement. Finally, extensive simulation experiments validate the effectiveness and superiority of the proposed model. This work can support decision-makers in developing new task plans in disruption scenarios and serve as a transition approach to enhance UWSoS resilience.

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Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).