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Role of Bio-Inspired Optimization in Disaster Operations Management Research

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Innovations in Bio-Inspired Computing and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 424))

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Abstract

Disaster Operations Management (DOM) is a Non deterministic polynomial, Multi-objective optimization problem. DOM is a cyclic process and holds various phases. It is impossible to prevent natural disasters completely but optimized solutions can be suggested to avoid/mitigate the impact of disasters. India is a developing country and natural disaster is one among the major issues in India. Due to various geo-climatic conditions, frequent natural disaster events like earthquake, flood, drought, landslides, tropical cyclone and storm strikes according to the vulnerability of the hazard prone area especially in the region of Tamil Nadu, India. DOM prevents human and economic losses by applying computer algorithms, computer based decision making tools and software solutions to handle disasters effectively. Still more improvisation is needed in an optimized pattern for acquiring best solutions. This paper presents the optimization perspective of DOM and highlights the need for bio inspired optimization techniques to reduce the impact of disasters, towards a social focus.

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References

  1. Rajput, A., Soni, R., Aharwal, R.P., Sharma, R.: Impact of data mining in drought monitoring. IJCSI Int. J. Comput. Sci. Issues 8(6), 2 (2011). ISSN (Online):1694-0814

    Google Scholar 

  2. Landström, C., Whatmore, S.J., Lane, S.N.: Virtual engineering: computer simulation modelling for flood risk management in England. J. Sci. Stud. 24(2), 3–22 (2011)

    Google Scholar 

  3. Chavan, S.D., Kulkarni, A.V., Adgokar, N.P.: Efficient bio-inspired method for disaster monitoring in wireless sensor networks using improved PSO. Int. Res. J. Eng. Technol. (IRJET) 2(4) (2015) e-ISSN:2395-0056, p-ISSN:2395-0072

    Google Scholar 

  4. Chavan, S.D., Kulkarni, A.V., Khot, T.S.: An efficient routing algorithm for lifetime enhancement in wireless sensor network using artificial bee colony algorithm. Int. Res. J. Eng. Technol. (IRJET) 2(4) (2015)

    Google Scholar 

  5. Chavan, S.D., Khot, T.S.: Efficient and reliable routing algorithm to enhance connectivity in disaster scenario: ABC algorithm. Int. J. Sci. Res. (IJSR) 4(5) (2013) ISSN (Online):2319-7064

    Google Scholar 

  6. Deepa, S., Ramachandran, G.: Disaster recovery system using seed block algorithm in cloud computing environment. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 5(2) (2015) ISSN:2277 128X

    Google Scholar 

  7. Kaisa, E.I., Hess, L., E.I., Alicia Benazir Portal Palomo, E.I.: An Emergency Evacuation planning model for special needs populations. J. Public Transport. 15(2) (2012)

    Google Scholar 

  8. Shafiq, F., Ahsan, K.: An ICT based early warning system for flood disasters in Pakistan. Res. J. Recent Sci. 3(9), 108–118 (2014) ISSN:2277-2502

    Google Scholar 

  9. GopalDatt.,Ashutosh Kumar Bhatt., Sunil Kumar: Disaster management information system framework using feed forward back propagation neural network. Int. J. Adv. Res. Comput. Commun. Eng. 4(3), (2015) ISSN(Online):2278-1021, ISSN(Print):2319-5940

    Google Scholar 

  10. Government of India National Institute of Disaster Management New Delhi. Report of Human Resource and Capacity Development Plan for Disaster Management and Risk Reduction in India (2013)

    Google Scholar 

  11. Government of India Ministry of Home Affairs. Report of Disaster Management in India (2011)

    Google Scholar 

  12. Han, M., Hakansson, J., Rebreyend, P.: How do different densities in a network affect the optimal location of service centres. Eur. J. Oper. Res. 15, (2013) ISSN:1650-5581

    Google Scholar 

  13. Wang, H., Li, X., Long, H., Qiao, Y., Li, Y.: Development and application of a simulation model for changes in land-use patterns under drought scenarios. Elsevier Comput. Geosci. 37, 831–843 (2011)

    Google Scholar 

  14. Jeeva, V.R., Jibi J Puthiyidam.: A survey on disaster management system. Int. J. Adv. Res. Comput. Sci. Manage. Stud. 2(11), (2014) ISSN:2321-7782

    Google Scholar 

  15. Liberatore, F., Ortun, M.T., Tirado, G., Vitoriano, B., Scaparra, M.P.: A hierarchical compromise model for the joint optimization of recovery operations and distribution of emergency goods in humanitarian logistics. Elsevier Comput. Oper. Res. 42, 3–31 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  16. Ramesh, M.V.: Real-time wireless sensor network for landslide detection. In: Third International Conference on Sensor Technologies and Applications (2009)

    Google Scholar 

  17. CamilaHoyos, M., Morales, R.S., Akhavan-Tabatabaei, R.: OR models with stochastic components in disaster operations management: A literature survey. Elsevier Comput. Ind. Eng. 82, 183–197 (2015)

    Google Scholar 

  18. Zhang, M.-X., Zhang, B., Zheng, Y.-J.,: Bio-Inspired metaheuristics for emergency transportation problems. Algorithms-Open Access J. 7, 15–31 (2014) ISSN:1999-4893

    Google Scholar 

  19. Alhazmi, O.H.: Computer-aided disaster recovery planning tools (CADRP). Int. J. Comput. Sci. Secur. (IJCSS) 9(3) (2015)

    Google Scholar 

  20. El-Anwar, O., El-Rayes, K., Elnashai, A.: An automated system for optimizing post-disaster temporary housing allocation. Elsevier Autom. Constr. 18, 983–993 (2009)

    Google Scholar 

  21. van Hentenryck, P.: Computational disaster management. In: Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence (2011)

    Google Scholar 

  22. Han, P., Wang, P.X., Zhang, S.Y., Zhu, D.: Drought forecasting based on the remote sensing data using ARIMA models. Elsevier Math. Comput. Model. 51, 1398–1403 (2010)

    Google Scholar 

  23. Subramanian, S.: Implementation of neural networks in flood forecasting. Int. J. Sci. Res. Publ. 2(10), (2012). ISSN:2250-3153

    Google Scholar 

  24. Renuka Devi, M., SanthoshBaboo, S.: Land use and land cover change detection for three decades: case study for Coimbatore area. Int. J. Eng. Res. Appl. (IJERA) 2(1), 1013-1028 (2012). ISSN:2248-9622

    Google Scholar 

  25. Renuka Devi, M., SanthoshBaboo, S.: Land use and land cover for one decade in Coimbatore dist using historical and recent high resolution satellite data. Int. J. Sci. Eng. Res. 3(2) (2012). ISSN:2229-5518

    Google Scholar 

  26. Saravana Kumar, J., Veeramani, R.: GPS Location alert system. IOSR J. Comput. Eng. (IOSR-JCE) 16(2), 36–42 (2014). Ver. IV, e-ISSN:2278-0661, p-ISSN:2278-8727

    Google Scholar 

  27. SonamLhamuBhutia, RatikaPradhan, Ghose, M.K.: A Survey on landslide susceptibility mapping using soft computing techniques. IOSR J. Appl. Geol. Geophys. (IOSR-JAGG) 3(1), 16–20 (2015). Ver. I, e-ISSN:2321-0990, p-ISSN:2321-0982

    Google Scholar 

  28. Stephen, A: Natural disasters in India with special reference to Tamil Nadu. J Acad. Ind. Res 1(2), (2012) ISSN:2278-521

    Google Scholar 

  29. Vyas, T., Desai, A.: Information technology for disaster management. In: Proceedings of National Conference on Computing for Nation Development, pp. 23–24 (2007)

    Google Scholar 

  30. Hristidis, V., Chen, S.-C., Li, T., Luis, S., Deng, Y.: Survey of data management and analysis in disaster situations. Elsevier J. Syst. Softw. 83, 1701–1714 (2010)

    Google Scholar 

  31. Varadharajan, A., Iyappan, L., Kasinathapandian, P.: Assessment on landuse changes in Coimbatore North taluk using image processing and geospatial techniques. Int. J. Eng. Res. Appl. (IJERA). 2(4), 233–237 (2012) ISSN:2248-9622

    Google Scholar 

  32. Boñgolan, V.P., Ballesteros., F.C., Jr., Banting, J.A.M., Olaes, A.M.Q., Aquino, C.R.: Metaheuristics in flood disaster management and risk assessment. In: Proceedings of 8th National conference on Information Technology Edu-cation (NCITE), pp. 20–23 (2010)

    Google Scholar 

  33. Zhenga, Y.-J., Chena, S.-Y., Ling, H.-F..: Evolutionary optimization for disaster relief operations: a survey. Elsevier Appl. Soft Comput. 27, 553–566 (2015)

    Google Scholar 

  34. Kothavala, Z.: Extreme precipitation events and the applicability of global climate models to the study of floods and droughts. Elsevier Math. Comput. Simul. 43, 261–268 (1997)

    Google Scholar 

  35. http://emdat.be/database

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Authors and Affiliations

  1. Department of Computer Applications, Bharathiar University, Coimbatore, Tamil Nadu, India

    R. Dhveya & T. Amudha

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  1. R. Dhveya
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  2. T. Amudha
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Correspondence to R. Dhveya .

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Editors and Affiliations

  1. Dep. of Computer Science, VŠB – Technical Univ. of Ostrava, Ostrava, Czech Republic

    Václav Snášel

  2. (MIR Labs), Scientific Net Innov & Res Excel, Auburn, Washington, USA

    Ajit Abraham

  3. Faculty of Elec. Eng. & Comp. Sci., VÅ B - Technical University of Ostrava, Ostrava-Poruba, Czech Republic

    Pavel Krömer

  4. Department of Paper Technology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Millie Pant

  5. Fac of Info & Comm, Comp Inte & Tech Lab, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia

    Azah Kamilah Muda

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Dhveya, R., Amudha, T. (2016). Role of Bio-Inspired Optimization in Disaster Operations Management Research. In: Snášel, V., Abraham, A., Krömer, P., Pant, M., Muda, A. (eds) Innovations in Bio-Inspired Computing and Applications. Advances in Intelligent Systems and Computing, vol 424. Springer, Cham. https://doi.org/10.1007/978-3-319-28031-8_50

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  • DOI: https://doi.org/10.1007/978-3-319-28031-8_50

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28030-1

  • Online ISBN: 978-3-319-28031-8

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