UML-Oriented Information Technology for Continuous Maximum Coverage Problems with Arbitrary-Shaped Objects
Abstract
Relevance. Continuous maximum coverage problems with arbitrary-shaped objects play a crucial role in geographic information systems, monitoring platforms, logistics services, security systems, spatial data analysis, and decision-support solutions. The growing volume of data, dynamic environments, and high model complexity require formalized, modular, and scalable information technologies. UML, as a modeling standard, enables formal architectural descriptions of software solutions, ensuring reliability, reproducibility, and transparency of implementation.
Purpose. To develop a UML-oriented information technology for solving continuous maximum coverage problems that incorporates an architectural model, data structures, information flows, functional components, and UML specifications of modules supporting coverage-based systems.
Methods. The study employs object-oriented and structural modeling techniques, UML diagramming (Use Case, Class, Activity, Sequence, Component, Composite Structure, State Machine, Deployment), architectural design methods, principles of modularity, dependency inversion, component decomposition, and approaches used in building scalable information systems.
Results. A complete UML specification of the architecture of an information technology for maximum coverage problems has been constructed: external interaction scenarios, classes, components, operation sequences, system behavior and state logic, infrastructural links, and deployment structure have been defined. An integrated three-tier architecture (presentation, application logic, and data layers) has been formed. Principles for constructing modules for spatial analytics, optimization, coverage criterion computation, scenario management, visualization, and data interfaces have been described. The UML models provide a formalized structure that enables the development of scalable and reproducible IT solutions for coverage problems.
Conclusions. The developed information technology provides structural, behavioral, and architectural formalization of a maximum coverage system. UML-oriented modeling improves architectural transparency, reduces risks of integration errors, and ensures scalability and reusability of components. The obtained UML models may serve as a methodological foundation for building intelligent GIS platforms, optimization services, monitoring systems, and real-time analytical solutions.
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P. Clements, F. Bachmann, L. Bass et al., Documenting Software Architectures: Views and Beyond, 2nd ed. Boston, MA, USA: Addison-Wesley, 2010, p. 624.
L. Bass, P. Clements, and R. Kazman, Software Architecture in Practice, 3rd ed. Boston, MA, USA: Addison-Wesley, 2012, p. 624.
R. N. Taylor, N. Medvidović, and E. M. Dashofy, Software Architecture: Foundations, Theory, and Practice. Hoboken, NJ, USA: Wiley, 2009, p. 736.
I. Rauf, M. Z. Iqbal, and Z. I. Malik, “UML based modeling of web service composition—A survey,” Int. J. Comput. Appl., vol. 1, no. 6, pp. 301–307, 2008. doi: 10.5120/324-524.
P. A. Longley, M. F. Goodchild, D. J. Maguire, and D. W. Rhind, Geographic Information Systems and Science, 3rd ed. Chichester, U.K.: Wiley, 2011, p. 560.
S. Gillies, Shapely: Computational Geometry Library, ver. 2.0.0. Zenodo, 2021. doi: 10.5281/zenodo.7428463.
K. Jordahl et al., “GeoPandas: Python tools for geographic data,” J. Open Source Softw., vol. 9, no. 1083, Art. no. 5660, Mar. 2023. doi: 10.21105/joss.05660.
J. Kennedy and R. Eberhart, “Particle swarm optimization,” in Proc. IEEE Int. Conf. Neural Netw. (ICNN'95), Perth, WA, Australia, 1995, vol. 4, pp. 1942–1948. doi: 10.1109/ICNN.1995.488968.
C. J. A. Bastos-Filho et al., “A novel search algorithm based on fish-school behavior,” IEEE Trans. Syst., Man, Cybern., B, Cybern., vol. 39, no. 2, pp. 237–252, Apr. 2009. doi: 10.1109/TSMCC.2009.2030235.
X.-S. Yang, Nature-Inspired Metaheuristic Algorithms, 2nd ed. Beckington, U.K.: Luniver Press, 2010, p. 148.
J. Nocedal and S. J. Wright, Numerical Optimization, 2nd ed. New York, NY, USA: Springer, 2006, p. 664. doi: 10.1007/978-0-387-40065-5.
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A. Calvagna, A. Gargantini, and E. Viganò, “An adaptive penalty based parallel tabu search for constrained covering array generation,” Inf. Softw. Technol., vol. 138, Art. no. 106768, Oct. 2021. doi: 10.1016/j.infsof.2021.106768.
J. Kallrath, “Cutting circles and polygons from area-minimizing rectangles,” J. Glob. Optim., vol. 43, no. 2–3, pp. 267–298, Jun. 2009. doi: 10.1007/s10898-007-9251-2.
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S. V. Yakovlev, “The concept of modeling packing and covering problems using modern computational geometry software,” Cybern. Syst. Anal., vol. 59, no. 1, pp. 108–119, Jan. 2023. doi: 10.1007/s10559-023-00547-5.
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S. Yakovlev, O. Kartashov, and D. Podzeha, “Mathematical models and nonlinear optimization in continuous maximum coverage location problem,” Computation, vol. 10, no. 7, Art. no. 119, Jul. 2022. doi: 10.3390/computation10070119.
S. Yakovlev, O. Kiseleva, D. Chumachenko, and D. Podzeha, “Maximum service coverage in business site selection using computer geometry software,” Electronics, vol. 12, no. 10, Art. no. 2329, May 2023. doi: 10.3390/electronics12102329.
S. Yakovlev et al., “Continuous maximum coverage location problem with arbitrary shape of service areas and regional demand,” Symmetry, vol. 17, no. 5, Art. no. 676, 2025. doi: 10.3390/sym17050676.
S. Yakovlev et al., “Optimization of mobile medical service locations based on predictive analytics in crisis scenarios,” in Proc. IADIS Inf. Syst. E-Soc., 2025, pp. 538–541.
K. Leichenko et al., “Assessment of the reliability of wireless sensor networks for forest fire monitoring systems considering fatal combinations of multiple sensor failures,” Cybern. Syst. Anal., vol. 61, no. 1, pp. 137–147, Jan. 2025. doi: 10.1007/s10559-025-00722-w.
S. Skorobohatko et al., “Architecture and reliability models of hybrid sensor networks for environmental and emergency monitoring systems,” Cybern. Syst. Anal., vol. 60, no. 2, pp. 293–304, Mar. 2024. doi: 10.1007/s10559-024-00670-x.
