Development of a mobile decision support system based on the smart method for android platform
DOI:
https://doi.org/10.15587/1729-4061.2019.168163Keywords:
mobile decision support system, decision maker, alternative, criteria, Smart method, three-layer architecture.Abstract
The work is devoted to the development of a mobile decision support system for solving the multiple criteria decision-making problems. To ensure the autonomous operation of the system, it was proposed to use a three-layer architecture. For reuse and distribution of the code, this model is implemented in three levels: presentation level, application level and data level.
The development of the application level in the developed mobile decision support system involves the creation of three subsystems: a decision-making subsystem, a database interaction subsystem and a message management subsystem. At the core of the decision-making subsystem of the developed mobile decision support system, an improved Smart method was chosen. This method differs from the classical Smart method in that the decision maker uses the elements of the decision matrix as estimates of each alternative for all criteria. Also, the nature of actions on the criteria (maximization or minimization) is taken into account. This, in turn, takes into account the normalization of elements of the decision matrix.
The startup of the database interaction subsystem, which is responsible for transferring and retrieving data to/from the database, occurs via the user interface. To create the database, the SQLite relational database management system was used. SQLite stores the entire database (including definitions, tables, indexes, and data) in one standard file on the device on which the application runs. The message management subsystem allows the decision maker to send the calculation results via the Internet or using the short message service (SMS).
The mobile decision support system has been developed in Java in Android Studio 3.2.1. The task of buying a smartphone was considered, as an application of the developed mobile decision support system.
References
- Mardani, A., Jusoh, A., MD Nor, K., Khalifah, Z., Zakwan, N., Valipour, A. (2015). Multiple criteria decision-making techniques and their applications – a review of the literature from 2000 to 2014. Economic Research-Ekonomska Istraživanja, 28 (1), 516–571. doi: https://doi.org/10.1080/1331677x.2015.1075139
- Kuznetsov, M. A., Ponomarev, S. S. (2009). Sovremennaya klassifikatsiya sistem podderzhki prinyatiya resheniy. Prikaspiyskiy zhurnal: upravlenie i vysokie tekhnologii, 3, 52–58.
- Power, D. J. (2000). Web-based and model-driven decision support systems: concepts and issues. 2000 Americas Conference on Information Systems (AMCIS), 2000. California.
- Guo, X., Díaz López, A. (2013). Mobile Decision Support System Usage in Organizations. 2013 19th Americas Conference on Information Systems (AMCIS), 2013. Chicago.
- Lisetskiy, Yu. M. (2017). DSS for selecting the elemental basis of corporate integrated information systems. Matematychni mashyny i systemy, 3, 23–37.
- Gaynanova, R. Sh., Shirokova, O. A. (2017). Sozdanie klient-servernyh prilozheniy. Vestnik Kazanskogo tekhnologicheskogo universiteta, 20 (3), 79–84.
- Bangui, H., Ge, M., Buhnova, B., Rakrak, S., Raghay, S., Pitner, T. (2017). Multi-Criteria Decision Analysis Methods in the Mobile Cloud Offloading Paradigm. Journal of Sensor and Actuator Networks, 6 (4), 25. doi: https://doi.org/10.3390/jsan6040025
- Shishkin, Yu. Е. (2017). Oblachnye servisy v sistemah podderzhki prinyatiya resheniy. Avtomatika. Vychislitel'naya tekhnika, 1 (14), 19–20.
- Tupalo, Y. (2017). Architecture of expert support and decision making system. Kompiuterni zasoby, merezhi ta systemy, 16, 146–155.
- Kostoglou, V., Kafkas, K. (2017). Design and development of an interactive mobile-based decision support system for selecting higher education studies. Balkan Region Conference on Engineering and Business Education, 3 (1), 240–248. doi: https://doi.org/10.1515/cplbu-2017-0032
- Ogunti, E. O., Akingbade, F. K., Segun, A., Oladimeji, O. (2018). Decision Support System Using Mobile Applications in the Provision of Day to Day Information about Farm Status to Improve Crop Yield. Periodicals of Engineering and Natural Sciences, 6 (2), 89–99.
- Obelets, T., Kiforenko, S. (2017). Mobile information system for decision support in diabetology applying cloud services. Mezhdunarodniy nauchniy zhurnal «Internauka», 8 (30), 56–59.
- Barigou, B. N., Barigou, F., Benchehida, C., Atmani, B., Belalem, G. (2018). The Design of a Cloud-based Clinical Decision Support System Prototype. International Journal of Healthcare Information Systems and Informatics, 13 (4), 28–48. doi: https://doi.org/10.4018/ijhisi.2018100103
- Lee, J. H., Ha, E. J., Baek, J. H., Choi, M., Jung, S. E., Yong, H. S. (2019). Implementation of Korean Clinical Imaging Guidelines: A Mobile App-Based Decision Support System. Korean Journal of Radiology, 20 (2), 182–189. doi: https://doi.org/10.3348/kjr.2018.0621
- Iphar, M., Alpay, S. (2018). A mobile application based on multi-criteria decision-making methods for underground mining method selection. International Journal of Mining, Reclamation and Environment, 1–25. doi: https://doi.org/10.1080/17480930.2018.1467655
- Ahmad, A., Li, K., Feng, C., Asim, S. M., Yousif, A., Ge, S. (2018). An Empirical Study of Investigating Mobile Applications Development Challenges. IEEE Access, 6, 17711–17728. doi: https://doi.org/10.1109/access.2018.2818724
- Perez, I. J., Cabrerizo, F. J., Herrera-Viedma, E. (2010). A Mobile Decision Support System for Dynamic Group Decision-Making Problems. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 40 (6), 1244–1256. doi: https://doi.org/10.1109/tsmca.2010.2046732
- Kozina, Y., Volkova, N., Horpenko, D. (2018). Mobile Application for Decision Support in Multi-Criteria Problems. 2018 IEEE Second International Conference on Data Stream Mining & Processing (DSMP). doi: https://doi.org/10.1109/dsmp.2018.8478499
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2019 Daniil Horpenko, Natalya Volkova, Marina Polyakova, Victor Krylov
This work is licensed under a Creative Commons Attribution 4.0 International License.
The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.
A license agreement is a document in which the author warrants that he/she owns all copyright for the work (manuscript, article, etc.).
The authors, signing the License Agreement with TECHNOLOGY CENTER PC, have all rights to the further use of their work, provided that they link to our edition in which the work was published.
According to the terms of the License Agreement, the Publisher TECHNOLOGY CENTER PC does not take away your copyrights and receives permission from the authors to use and dissemination of the publication through the world's scientific resources (own electronic resources, scientometric databases, repositories, libraries, etc.).
In the absence of a signed License Agreement or in the absence of this agreement of identifiers allowing to identify the identity of the author, the editors have no right to work with the manuscript.
It is important to remember that there is another type of agreement between authors and publishers – when copyright is transferred from the authors to the publisher. In this case, the authors lose ownership of their work and may not use it in any way.
