Selection of Equipment Reserve Sites in Coastal Areas Based on Fuzzy Multi-Attribute Decision Making

DOI: https://doi.org/10.62517/jsse.202608104

Author(s)

Ronghai Liu

Affiliation(s)

Engineering University of PAP, Xi’an, China

Abstract

Addressing the complexities inherent in the coastal regions of China—characterized by intricate geographic conditions, escalating demands for emergency support, and the widespread deployment of unmanned systems—this study confronts critical challenges such as ambiguous information, conflicts in multi-objective decision-making, and the difficulties in adapting to dynamic constraints during the site selection for equipment reserve sites. We propose an innovative site selection methodology that synthesizes fuzzy multi-attribute decision-making with dynamic constraint adaptation. Initially, grounded in the realities of a comprehensive coastal defense system, low-altitude security, and unmanned system management requirements, a six-dimensional evaluation indicator system is established, encompassing support timeliness, strike resilience, unmanned system adaptability, logistical sustainability, regional coverage, and construction and deployment costs. Subsequently, intuitionistic fuzzy set theory is employed to address the fuzziness and uncertainty of site selection criteria. By extracting weighted assessments from domain experts and devising an enhanced fuzzy consensus measurement model, efficient decision consensus is achieved. Finally, typical coastal regions including Pingtan, Ningde, Shantou, Xiangshan, and Zhangzhou serve as candidate sites for empirical analysis, integrating actual shoreline distribution, security control, and geographical data. The results demonstrate that the proposed method effectively amalgamates dynamic risk information, environmental constraints, and support requirements specific to coastal areas, objectively quantifies each reserve point’s overall support efficacy, and yields optimized selections that align closely with regional equipment forward-deployment strategies, emergency material reserves, and comprehensive rapid response system construction. This provides a scientific decision-making foundation for the optimization of China’s coastal equipment reserve system and the enhancement of its routine support capabilities.

Keywords

Equipment Reserve Sites; Fuzzy Multi-Attribute Decision Making; Consensus Mechanism; Multi-Objective Evaluation; Adversarial Constraints

References

[1] ZADEH L A. Fuzzy sets. Information and Control, 1965, 8(3): 338-353. [2] BELLMAN R E, ZADEH L A. Decision-making in a fuzzy environment. Management Science, 1970, 17(4): B141-B164. [3] YAGER R R. On ordered weighted averaging aggregation operators in multicriteria decision making. IEEE Transactions on Systems, Man, and Cybernetics, 1988, 18(1): 183-190. [4] SAATY T L. The analytic hierarchy process. New York: McGraw-Hill, 1980. [5] Xu Zeshui. Theory and Methods of Fuzzy Multi-Attribute Decision Making. Beijing: Science Press, 2013. [6] Wang Shenping, Li Jianhua, Du Min, et al. Equipment Reserve Warehouse Location Model Based on Two-Stage Generalized Maximum Coverage. Journal of Ordnance Equipment Engineering, 2020, 41(3): 41-45. [7] LIU L, ZHU Q, YANG D, et al. Extended Multicriteria Group Decision Making with a Novel Aggregation Operator for Emergency Material Supplier Selection. Entropy, 2023, 25(4): 702. [8] KUMAR A, DIXIT V, SHARMA A. Fuzzy multi-criteria decision analysis for coastal emergency facility location planning under climate uncertainty. Sustainable Cities and Society, 2021, 76: 103428. [9] ZHOU X, WANG Y, XU Z. Dynamic intuitionistic fuzzy multi-attribute decision making with risk coupling consideration for emergency response. IEEE Transactions on Fuzzy Systems, 2022, 30(10): 4217-4228. [10] PEREIRA L A, COSTA H G. Multi-objective fuzzy multi-attribute decision making for integrated infrastructure planning: A practical framework. European Journal of Operational Research, 2020, 287(2): 612-627. [11] ZHANG Z, GUO S, MARTINEZ L. Consensus reaching for large-scale group decision making with fuzzy preference relations: A dynamic clustering approach. Information Fusion, 2023, 91: 327-341. [12] OZCAN E, EROGLU S. Fuzzy multi-attribute decision making for military equipment storage site selection under uncertainty. Journal of Defense Modeling and Simulation, 2022, 19(3): 345-358.