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A new location-allocation-problem for mobile telecommunication rigs model under crises and natural disasters: a real case study

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Abstract

With the improvement of mobile technology, the importance of the communication industry and telecommunication transmission facilities has grown, and the number of subscribers has increased gradually. That is why the issue of covering mobile telecommunication rigs and telecommunication facilities is important. Locating rigs in suitable places and reinforcing them during crises and natural disasters can be helpful for users, especially in places with poor signal strength. In addition, by the efficient allocation of rigs to suitable locations, areas with a high population are eliminated at base stations. In this paper, a novel Mixed-Integer Non-Linear Programming (MINLP) model is presented to cover and allocate base mobile telecommunication rigs optimally under critical conditions in different locations. In order to evaluate the performance of the proposed model, the LP-metric method is used for small-sized problems, while a simulated annealing algorithm is applied for large-sized problems. To tune of the parameter's algorithm, Taguchi method is used. Several test instances are suggested to evaluate the efficiency of the suggested solution methods. The proposed model is also implemented in a case study to show its usefulness and performance in practice. Eventually, the optimal network presented in the case study is explained.

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References

  • Ahmadi Choukolaei H, Jahangoshai Rezaee M, Ghasemi P, Saberi M (2021) Efficient crisis management by selection and analysis of relief centers in disaster integrating GIS and multicriteria decision methods: a case study of Tehran. Math Probl Eng

  • Amiri-Aref M, Javadian N, Tavakkoli-Moghaddam R, Baboli A (2013) A new mathematical model for the Weber location problem with a probabilistic polyhedral barrier. Int J Prod Res 51(20):6110–6128

    Article  Google Scholar 

  • Araujo, F. C., & Borges, M. R. (2012, May). Support for systems development in mobile devices used in emergency management. In Proceedings of the 2012 IEEE 16th International Conference on Computer Supported Cooperative Work in Design (CSCWD), pp. 200–206. IEEE.

  • Balakrishnan H, Deo N (2006). Discovering communities in complex networks. In Proceedings of the 44th annual Southeast regional conference, pp. 280–285

  • Butt SE, Cavalier TM (1997) Facility location in the presence of congested regions with the rectilinear distance metric. Socio-Econ Plan Sci 31(2):103–113

    Article  Google Scholar 

  • Church RL, Scaparra MP (2007) Protecting critical assets: the r-interdiction median problem with fortification. Geogr Anal 39(2):129–146

    Article  Google Scholar 

  • Demiane F, Sharafeddine S, Farhat O (2020) An optimized UAV trajectory planning for localization in disaster scenarios. Comput Netw 179:107378

    Article  Google Scholar 

  • Eiselt HA, Marianov V (2012) Mobile phone tower location for survival after natural disasters. Eur J Oper Res 216(3):563–572

    Article  MathSciNet  Google Scholar 

  • Erdemir ET, Batta R, Spielman S, Rogerson PA, Blatt A, Flanigan M (2008) Location coverage models with demand originating from nodes and paths: application to cellular network design. Eur J Oper Res 190(3):610–632

    Article  MathSciNet  Google Scholar 

  • Ghasemi P, Khalili-Damghani K (2021) A robust simulation-optimization approach for pre-disaster multi-period location–allocation–inventory planning. Math Comput Simul 179:69–95

    Article  MathSciNet  Google Scholar 

  • Ghasemi P, Khalili-Damghani K, Hafezalkotob A, Raissi S (2019) Uncertain multi-objective multi-commodity multi-period multi-vehicle location-allocation model for earthquake evacuation planning. Appl Math Comput 350:105–132

    MathSciNet  MATH  Google Scholar 

  • Ghasemi P, Khalili-Damghani K, Hafezalkotob A, Raissi S (2020) Stochastic optimization model for distribution and evacuation planning (A case study of Tehran earthquake). Socio-Econ Plan Sci 71:100745

    Article  Google Scholar 

  • Goodarzian F, Hosseini-Nasab H, Muñuzuri J, Fakhrzad MB (2020) A multi-objective pharmaceutical supply chain network based on a robust fuzzy model: a comparison of meta-heuristics. Appl Soft Comput 92:106331

    Article  Google Scholar 

  • Goodarzian F, Hoseini-Nasab H, Toloo M, Fakhrzad MB (2021a) Designing a new Medicine Supply Chain Network considering production technology policy using two novel heuristic algorithms. RAIRO Recherche Opérationnelle 55:1015

    MathSciNet  Google Scholar 

  • Goodarzian F, Kumar V, Abraham A (2021b) Hybrid meta-heuristic algorithms for a supply chain network considering different carbonission regulations using big data characteristics. Soft Comput 25(11):7527–7557

    Article  Google Scholar 

  • Goodarzian F, Kumar V, Ghasemi P (2021c) A set of efficient heuristics and meta-heuristics to solve a multi-objective pharmaceutical supply chain network. Comput Ind Eng 158:107389

    Article  Google Scholar 

  • Goodarzian F, Shishebori D, Nasseri H, Dadvar F (2021d) A bi-objective production-distribution problem in a supply chain network under grey flexible conditions. RAIRO Oper Res 55:S1287–S1316

    Article  MathSciNet  Google Scholar 

  • Goodarzian F, Wamba SF, Mathiyazhagan K, Taghipour A (2021e) A new bi-objective green medicine supply chain network design under fuzzy environment: hybrid metaheuristic algorithms. Comput Ind Eng 160:107535

    Article  Google Scholar 

  • Hamacher HW, Nickel S (1998) Classification of location models. Locat Sci 6(1–4):229–242

    Article  Google Scholar 

  • Jiang J, Lai TH, Soundarajan N (2002) On distributed dynamic channel allocation in mobile cellular networks. IEEE Trans Parallel Distrib Syst 13(10):1024–1037

    Article  Google Scholar 

  • Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by simulated annealing. Science 220(4598):671–680

    Article  MathSciNet  Google Scholar 

  • Kremlin H (2007). Telecom day, challenges in the mobile telecommunication industry, SIAM News, Volume 40, Number 8, Oct.2007

  • Lemamou EA, Chamberland S, Galinier P (2013) A reliable model for global planning of mobile networks. Comput Oper Res 40(10):2270–2282

    Article  Google Scholar 

  • Li Q, Zeng B, Savachkin A (2013) Reliable facility location design under disruptions. Comput Oper Res 40(4):901–909

    Article  MathSciNet  Google Scholar 

  • Liu K, Peng J, He L, Pan J, Li S, Ling M, Huang Z (2019) An active mobile charging and data collection scheme for clustered sensor networks. IEEE Trans Veh Technol 68(5):5100–5113

    Article  Google Scholar 

  • Maleki HR, Karimidehkordi E (2016) Mobile base stations location problem to fortification against natural disasters: a fuzzy approach. J Intell Fuzzy Syst 30(3):1421–1427

    Article  Google Scholar 

  • Mathar R, Niessen T (2000) Optimum positioning of base stations for cellular radio networks. Wirel Netw 6(6):421–428

    Article  Google Scholar 

  • Monakhov YM, Monakhov MY, Telny AV (2019, April). Improving the accuracy of local positioning for mobile network nodes using satellite navigation systems. In 2019 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT), pp. 424–427). IEEE

  • Morales-Castaneda B, Zaldivar D, Cuevas E, Maciel-Castillo O, Aranguren I, Fausto F (2019) An improved Simulated Annealing algorithm based on ancient metallurgy techniques. ApplSoft Comput 84:105761

    Google Scholar 

  • Ou CH (2011) A localization scheme for wireless sensor networks using mobile anchors with directional antennas. IEEE Sens J 11(7):1607–1616

    Article  Google Scholar 

  • Preece G, Shaw D, Hayashi H (2015) Application of the Viable System Model to analyse communications structures: a case study of disaster response in Japan. Eur J Oper Res 243(1):312–322

    Article  Google Scholar 

  • Simpson T (2012) Optimal location of mobile telecommunication masts. a case study of cape coast metropolitan area (Doctoral dissertation)

  • Støttrup-Andersen U (2009) Masts and towers. In: Symposium of the international association for shell and spatial structures (50th. 2009. Valencia). Evolution and trends in design, analysis and construction of shell and spatial structures: proceedings. Editorial Universitat Politècnica de València

  • Taguchi G (1986) Introduction to quality engineering: designing quality into products and processes (No. 658.562 T3)

  • Teterin V, Hurley S (2014) Optimized network dimensioning and planning for WiMAX technology. Ad Hoc Netw 13:381–403

    Article  Google Scholar 

  • Tutschku K (1998) Demand-based radio network planning of cellular mobile communication systems. In Proceedings. IEEE INFOCOM'98, the Conference on Computer Communications. Seventeenth Annual Joint Conference of the IEEE Computer and Communications Societies. Gateway to the 21st Century (Cat. No. 98 (Vol. 3, pp. 1054–1061). IEEE.

  • Wei L, Zhang Z, Zhang D, Leung SC (2018) A simulated annealing algorithm for the capacitated vehicle routing problem with two-dimensional loading constraints. Eur J Oper Res 265(3):843–859

    Article  MathSciNet  Google Scholar 

  • Yang L, Lu YZ, Zhong YC, Yang SX (2018) An unequal cluster-based routing scheme for multi-level heterogeneous wireless sensor networks. Telecommun Syst 68(1):11–26

    Article  Google Scholar 

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Authors and Affiliations

  1. School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

    Fariba Goodarzian

  2. Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research Excellence, 11, 3rd Street NW, P.O. Box 2259. Auburn, Washington, 98071, USA

    Fariba Goodarzian

  3. Department of Industrial Management, Faculty of Administrative Sciences and Economics, Arak University, Arak, Iran

    Farzad Bahrami

  4. Department of Industrial Engineering, Yazd University, Yazd, Iran

    Davood Shishebori

Authors
  1. Fariba Goodarzian
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  2. Farzad Bahrami
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  3. Davood Shishebori
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Correspondence to Fariba Goodarzian or Farzad Bahrami.

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Goodarzian, F., Bahrami, F. & Shishebori, D. A new location-allocation-problem for mobile telecommunication rigs model under crises and natural disasters: a real case study. J Ambient Intell Human Comput 13, 2565–2583 (2022). https://doi.org/10.1007/s12652-021-03461-w

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  • DOI: https://doi.org/10.1007/s12652-021-03461-w

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