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Article

Research on Warship System Resilience Based on Intelligent Recovery with Improved Ant Colony Optimization

1
Ocean College, Jiangsu University of Science and Technology, No. 2 MengXi Road, JingKou District, Zhenjiang 212003, China
2
Reliability and Systems Engineering Open Group, No. 2 MengXi Road, JingKou District, Zhenjiang 212003, China
3
Institute of Software Chinese Academy of Science, No. 4 South Fourth Street, Zhongguancun, Beijing 100190, China
*
Authors to whom correspondence should be addressed.
Algorithms 2025, 18(10), 626; https://doi.org/10.3390/a18100626
Submission received: 22 August 2025 / Revised: 27 September 2025 / Accepted: 30 September 2025 / Published: 3 October 2025
(This article belongs to the Special Issue Evolutionary and Swarm Computing for Emerging Applications)

Abstract

Faced with complex, ever-changing battlefield environments and diverse attacks, enabling warship combat systems to recover rapidly and effectively after damage is key to enhancing resilience and sustained combat capability. We construct a representative naval battle scenario and propose an integrated Attack-Defense-Recovery Strategy (ADRS) grounded in warship system models for different attack types. To address high parameter sensitivity, weak initial pheromone feedback, suboptimal solution quality, and premature convergence in traditional ant colony optimization (ACO), we introduce three improvements: (i) grid-search calibration of key ACO parameters to enhance global exploration, (ii) a non-uniform initial pheromone mechanism based on the wartime importance of equipment to guide early solutions, and (iii) an ADRS-consistent state-transition rule with group-based starting points to prioritize high-value equipment during the search. Simulation results show that the improved ACO (IACO) outperforms classical ACO in convergence speed and solution optimality. Across torpedo, aircraft/missile, and UAV scenarios, ADRS-ACO improves over GRS-ACO by 7.2%, 0.3%, and 5.5%, while ADRS-IACO achieves gains of 34.9%, 17.1%, and 16.7% over GRS-ACO and 25.9%, 16.7%, and 10.6% over ADRS-ACO. Overall, ADRS-IACO consistently delivers the best solutions. In high-intensity, high-damage torpedo conditions, ADRS-IACO demonstrates superior path planning and repair scheduling, more effectively identifying critical equipment and allocating resources. Moreover, under multi-wave combat, coupling with ADRS effectively reduces cumulative damage and substantially improves overall warship-system resilience.
Keywords: system resilience; system recovery; ant colony optimization; warship system system resilience; system recovery; ant colony optimization; warship system

Share and Cite

MDPI and ACS Style

Li, Z.; Wang, L.; Meng, L.; Yang, G. Research on Warship System Resilience Based on Intelligent Recovery with Improved Ant Colony Optimization. Algorithms 2025, 18, 626. https://doi.org/10.3390/a18100626

AMA Style

Li Z, Wang L, Meng L, Yang G. Research on Warship System Resilience Based on Intelligent Recovery with Improved Ant Colony Optimization. Algorithms. 2025; 18(10):626. https://doi.org/10.3390/a18100626

Chicago/Turabian Style

Li, Zhen, Luhong Wang, Lingzhong Meng, and Guang Yang. 2025. "Research on Warship System Resilience Based on Intelligent Recovery with Improved Ant Colony Optimization" Algorithms 18, no. 10: 626. https://doi.org/10.3390/a18100626

APA Style

Li, Z., Wang, L., Meng, L., & Yang, G. (2025). Research on Warship System Resilience Based on Intelligent Recovery with Improved Ant Colony Optimization. Algorithms, 18(10), 626. https://doi.org/10.3390/a18100626

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