Nature Inspired Based Meta-heuristic Techniques
for Global Applications
Authors: Rachhpal Singh, India
Meta-heuristic techniques are becoming popular tools in some of the recent years and
are used and applied in many fields globally. The different algorithms of meta-heuristic are
best for optimization and solving problems in very easy format in all the real-world,
engineering, mathematics, data science, image processing like area. This paper is a simple
review of various nature inspired meta-heuristic techniques in different fields for better
optimization..
Keywords: Genetic Algorithm, Particle Swarm Optimization, Variable Neighbourhood Search, Nature Inspired Algorithms, Cloud Computing, Mobile Cloud Computing, Job Scheduling, Health Care System.
References
[1] Diego Oliva, Salvador Hinojosa and M V Demeshko, “Engineering applications of metaheuristics: an introduction”, Journal of Physics: Conference series, International conference on Information Technologies in Business and Industry 2016, Vol. 803, pp.21-26.
[2] AnupriyaGogna and AkashTayal, “Metaheuristics: review and application”, Journal of Experimental and Theoretical Artificial Intelligence, Volume 25, Issue 4, 2013, pp. 503-526.
[3] R.J. Kuo, P.H. Kuo, Yi RueiChen, F.E. Zulvia, “Application of metaheuristics-based clustering algorithm to item assignment in a synchronized zone order picking system”, Applied Soft Computing, 2016, Vol. 46, pp. 143-150.
[4] H. T. Dinh, C. Lee, D. Niyatoand P. Wang. (2013) A survey of mobile cloud computing: Architecture, applications, and approaches. Wireless Commun. Mobile Comput.13(18): 1587-1611.
[5] Wang, Xiaoliang, and Zhanpeng Jin. (2019) An Overview of Mobile Cloud Computing for Pervasive Healthcare. IEEE Access7(1): 66774- 66791.
[6] Singh, Rachhpal, and Rupinder Singh. "Nature Inspired Job Scheduling For E-Health Services In Mobile Cloud Computing."International Journal of Computer Applications & Information Technology, Vol. 11, Issue No. 2, 2019.
[7] J. H. Abawajy and M. M. Hassan. (2017) Federated Internet of Things and cloud computing pervasive patient health monitoring system.IEEE Commun. Mag.55(1):48-53.
[8] H. Jemal, Z. Kechaou, M. B. Ayed, and A. M. Alimi,. (2015) Cloud computing and mobile devices based system for healthcare application.Proc.IEEE Int. Symp. Technol. Soc. (ISTAS). 1(1):1-5.
[9] Rachhpal Singh, “Genetic-variable neighborhood search with thread replication for mobile cloud computing” International Journal of Parallel Emergent and Distributed Systems, 32(5):1-16 • June 2016.
[10] A. T. Lo'ai, R. Mehmood, E. Benkhlifa, and H. Song.(2016) Mobile cloud computing model and big data analysis for healthcare applications.IEEE Access, 4(1): 6171-6180.
[11] Y. Li, M. Chen, W. Dai, and M. Qiu. (2017) Energy optimization with dynamic task scheduling mobile cloud computing,IEEE Syst. J.11(1):96-105.
[12] F. Dong and S.G. Akl.(2006) Scheduling algorithms for grid computing: State of the art and open problems, Technical Report - Queen's University, 2006(1): 1-504.
[13] Sharma, M., G. Singh, and R. Singh. (2018) Clinical decision support system query optimizer using hybrid Firefly and controlled Genetic Algorithm. Journal of King Saud University-Computer and Information Sciences.
[14] Kaur, Prableen, and Manik Sharma. (2017) A survey on using nature inspired computing for fatal disease diagnosis.International Journal of Information System Modeling and Design (IJISMD), 8(2):70-91.
[15] Sharma, Manik and Romero, Natalia. (2018) Future Prospective of Soft Computing Techniques in Psychiatric Disorder Diagnosis. EAI Endorsed Transactions on Pervasive Health and Technology. 18(15):1-3.
[16] W. Pang, K. Wang, C. Zhou. (2004) Fuzzy discrete particle swarm optimization for solving traveling salesman problem, Proceedings of the 4th International Conference on Computer and Information Technology IEEE CS Press.
[17] M. Clerc and J. Kennedy.(2002) The particle swarm-explosion, stability, and convergence in a multidimensional complex space, IEEE Transactions on evolutionary Computation6:58-73.
[18] Sharma Manik, Gurvinder Singh and Rajinder Singh. (2019) An Advanced Conceptual Diagnostic Healthcare Framework for Diabetes and Cardiovascular Disorders. arXiv preprint arXiv:1901.10530.
[19] Sharma, Manik, and Gurvinder Singh. (2019) Need and Design of Smart and Secure Energy-Efficient IoT-Based Healthcare Framework. In Energy Conservation for IoT Devices, 1:259-281.
[20] Igor Stojanovic, IvonaBrajevic, Predrag S. Stanimirovic, Lev A. Kazakovtsev and ZoranZdravev, “Application of Heuristic and MetaheuristicAlgorithms in Solving Constrained Weber Problem with Feasible Region Bounded by Arcs”, Evolutionary Algorithms and Metaheuristics: Applications in Engineering Design and Optimization, Volume 2017.
[21] Sharma, Manik, and PrableenKaur. "A Comprehensive Analysis of Nature-Inspired Meta-Heuristic Techniques for Feature Selection Problem." Archives of Computational Methods in Engineering (2020): 1-25.
[22] Sharma, Manik, and Natalia Romero. "Future prospective of soft computing techniques in psychiatric disorder diagnosis."EAI Endorsed Transactions on Pervasive Health and Technology 4.15 (2018).
[23] Kaur, Prableen, and Manik Sharma. "A survey on using nature inspired computing for fatal disease diagnosis." International Journal of Information System Modeling and Design (IJISMD)8.2 (2017): 70-91.
[24] Sharma, Samriti, Manik Sharma, and Gurvinder Singh. "A chaotic and stressed environment for 2019-nCoV suspected, infected and other people in India: Fear of mass destruction and causality." Asian Journal of Psychiatry 51 (2020): 102049.
[25] Sharma, Manik, Gurvinder Singh, and Rajinder Singh. "An advanced conceptual diagnostic healthcare framework for diabetes and cardiovascular disorders." arXiv preprint arXiv:1901.10530 (2019).
[26] Kaur, Prableen, and Manik Sharma. "Analysis of data mining and soft computing techniques in prospecting diabetes disorder in human beings: a review." Int. J. Pharm. Sci. Res 9 (2018): 2700-2719.
[27] Gautam, Ritu, and Manik Sharma. "Prevalence and Diagnosis of Neurological Disorders Using Different Deep Learning Techniques: A Meta-Analysis." Journal of Medical Systems44.2 (2020): 49.
[28] Sharma, M., G. Singh, and R. Singh. "Clinical decision support system query optimizer using hybrid Firefly and controlled Genetic Algorithm." Journal of King Saud University-Computer and Information Sciences (2018).
[29] Sharma, Manik, et al. "Analysis of DSS queries using entropy based restricted genetic algorithm." Applied Mathematics & Information Sciences 9.5 (2015): 2599.
[30] Sharma, Manik, Gurvinder Singh, and Rajinder Singh. "A review of different cost-based distributed query optimizers."Progress in Artificial Intelligence 8.1 (2019): 45-62.
[31] Sharma, Manik. "Role and Working of Genetic Algorithm in Computer Science." International Journal of Computer Applications and Information Technology (IJCAIT) 2.1 (2013).
[32] Sharma, Manik, Gurvinder Singh, and Rajinder Singh. "Design of GA and Ontology based NLP Frameworks for Online Opinion Mining." Recent Patents on Engineering 13.2 (2019): 159-165.
[33] Begur, Sachidanand V., David M. Miller, and Jerry R. Weaver. (1997) An integrated spatial DSS for scheduling and routing home-health-care nurses. Interfaces 27, 4: 35-48.
[34] Thompson, Bruce J., Glenda D. Graves, and Delmur R. Mayhak Jr. (2008) Method and system for scheduling employees in a patient care environment." U.S. Patent, 7,457,765.
[35] Fikar, Christian, and Patrick Hirsch. (2017) Home health care routing and scheduling: A review.Computers & Operations Research, 77: 86-95.
[36] Othman, Sarah Ben, HayfaZgaya, Slim Hammadi, Alain Quilliot, Alain Martinot, and Jean-Marie Renard. (2016) Agents endowed with uncertainty management behaviors to solve a multiskill healthcare task scheduling.Journal of biomedical informatics, 64: 25-43.
[37] Barg-Walkow, Laura H., and Wendy A. Rogers. (2017) Modeling task scheduling in complex healthcare environments: Identifying relevant factors.Proceedings of the Human Factors and Ergonomics Society Annual MeetingSage CA: Los Angeles, CA: SAGE Publications, 61(1):772-775.
[38] Abdelaziz, Ahmed, Mohamed Elhoseny, Ahmed S. Salama, and A. M. Riad. (2018) A machine learning model for improving healthcare services on cloud computing environment, Measurement, 119:117-128.
[39] Abdelaziz, Ahmed, Mohamed Elhoseny, Ahmed S. Salama, Alaa Mohamed Riad, and Aboul Ella Hassanien. (2017), Intelligent algorithms for optimal selection of virtual machine in cloud environment, towards enhance healthcare services.International Conference on Advanced Intelligent Systems and InformaticsSpringer Cham, 289-298.
[40] Islam, MdMofijul, MdAbdurRazzaque, Mohammad Mehedi Hassan, Walaa Nagy Ismail, and Biao Song. (2017) Mobile cloud-based big healthcare data processing in smart cities. IEEE Access ,5:11887-11899.
[41] Elhoseny, Mohamed, Ahmed Abdelaziz, Ahmed S. Salama, Alaa Mohamed Riad, Khan Muhammad, and Arun Kumar Sangaiah. (2018) A hybrid model of internet of things and cloud computing to manage big data in health services applications.Future generation computer systems, 86:1383-1394.
[42] Marynissen, Joren, and Erik Demeulemeester. (2019) Literature review on multi-appointment scheduling problems in hospitals. European Journal of Operational Research, 272(2):407-419.
[43] Moreira, Mário WL, Joel JPC Rodrigues, Neeraj Kumar, Jalal Al-Muhtadi, and Valery Korotaev. (2018) Nature-inspired algorithm for training multilayer perceptron networks in e-health environments for high-risk pregnancy care. Journal of medical systems, 42(3)):51.
[44] Samanta, S. O. U. R. A. V., A. L. K. O. P. A. R. N. A. Choudhury, N. Dey, A. S. Ashour, and V. E. Balas. (2017) Quantum-inspired evolutionary algorithm for scaling factor optimization during manifold medical information embedding.In Quantum Inspired Computational Intelligence, :285-326.
[45] Zhang, Yudong, Shuihua Wang, and GenlinJi. (2015) A comprehensive survey on particle swarm optimization algorithm and its applications.Mathematical Problems in Engineering.
[46] Liu, Weibo, Zidong Wang, Xiaohui Liu, NianyinZeng, and David Bell. (2018) A novel particle swarm optimization approach for patient clustering from emergency departments, IEEE Transactions on Evolutionary Computation.
[47] Gautam, Ritu, PrableenKaur, and Manik Sharma. (2019) A comprehensive review on nature inspired computing algorithms for the diagnosis of chronic disorders in human beings. Progress in Artificial Intelligence:1-24.
