Web­oriented decision support system for planning agreements execution

Authors

DOI:

https://doi.org/10.15587/1729-4061.2018.132604

Keywords:

web-oriented decision support system, agreements execution planning, combined algorithm, programming module

Abstract

The problem of construction of the web-based decision support system when planning the execution of agreements at service-rendering enterprises is considered. Characteristics of operations of such enterprises are explored. The improved mathematical model for the problem of agreements execution planning was constructed and the criteria for evaluation of effectiveness of the resulting variant of the solution were determined. The use of the additive convolution of a particular criterion with setting priorities of meeting each of them was applied as estimation of effectiveness of execution variant. The combined algorithm for solving the problem on planning was developed, aimed at taking into account the features of the subject area. In order to use the combined algorithm, it is proposed to represent the input data in the form of a multi-layer graph, each layer of which corresponds to the working time of one executor, and nodes determine the synchronization points between the layers. During designing a combined algorithm, the elements of the ACO algorithm and of the genetic algorithm were used. The DSS structure for agreement execution planning was proposed, and the technologies, used for its implementation, were considered. The users’ interface of the system was presented. The developed decision support system provides support for the management functions during planning and enables the in-depth analysis of situations, their evaluation and selection of the optimal variant of the plan, performing all preparatory actions and forming ready solutions. The created system is web-based, which allows using it at any place with the Internet access.

Author Biographies

Serhii Hrybkov, National University of Food Technologies Volodymyrska str., 68, Kyiv, Ukraine, 01601

PhD, Associate Professor

Department of Information Systems

Hanna Oliinyk, National University of Food Technologies Volodymyrska str., 68, Kyiv, Ukraine, 01601

Postgraduate student

Department of Information Systems

Valery Litvinov, Institute of Mathematical Machines and Systems Problems of NASU Akademika Hlushkova ave., 42, Kyiv, Ukraine, 03187

Doctor of Technical Sciences, Professor, Lead Researcher

References

  1. Hrybkov, S. V., Lytvynov, V. A., Oliinyk, H. V. (2015). Zadacha planuvannia vykonannia dohovoriv ta pidkhody do yii efektyvnoho vyrishennia. Matematicheskie mashiny i sistemy, 2, 61–70.
  2. Bakshi, T., Sarkar, B., Sanyal, S. K. (2012). An Evolutionary Algorithm for Multi-criteria Resource Constrained Project Scheduling Problem based On PSO. Procedia Technology, 6, 231–238. doi: 10.1016/j.protcy.2012.10.028
  3. Chastikova, V. A., Vlasov, K. A. (2013). Razrabotka i sravnitel'nyy analiz evristicheskih algoritmov dlya poiska naimen'shego gamil'tonova cikla v polnom grafe. Fundamental'nye issledovaniya, 10, 63–67.
  4. Santosh, K. S., Vinod, K. G. (2015). Genetic Algorithms: Basic Concepts and Real World Applications. International Journal of Electrical, Electronics and Computer Systems (IJEECS), 3 (12), 116–123.
  5. Senthilkumar, K. M., Selladurai, V., Raja, K., Thirunavukkarasu, V. (2011). A Hybrid Algorithm Based on PSO and ACO Approach for Solving Combinatorial Fuzzy Unrelated Parallel Machine Scheduling Problem. European Journal of Scientific Research, 64 (2), 293.
  6. Hrybkov, S. V., Oliinyk, H. V. (2017). Modyfikovanyi ACO alhorytm pobudovy kalendarnoho planu vykonannia dohovoriv. Matematychne ta kompiuterne modeliuvannia. Seriya: Tekhnichni nauky, 15, 156–162.
  7. Emine, A., Tugba, S. (2012). A Variable Capacity Parallel Machine Scheduling Problem. Proceedings of the 2012 International Conference on Industrial Engineering and Operations Management, 548–554.
  8. Rodriguez, F. J., Lozano, M., García-Martínez, C., González-Barrera, J. D. (2013). An artificial bee colony algorithm for the maximally diverse grouping problem. Information Sciences, 230, 183–196. doi: 10.1016/j.ins.2012.12.020
  9. Sivaraj, R., Ravichandran, T., Devi Priya, R. (2012). Boosting Performance of genetic algorithm through Selective initialization. European Journal of Scientific Research, 68 (1), 93–100.
  10. Shafiei Nikabadi, M., Naderi, R. (2016). A hybrid algorithm for unrelated parallel machines scheduling. International Journal of Industrial Engineering Computations, 681–702. doi: 10.5267/j.ijiec.2016.2.004
  11. Pankratiev, E. V., Chepovskiy, A. M., Cherepanov, E. A., Chernyshev, S. V. (2005). Algorithms and Methods for Solving Scheduling Problems and Other Extremum Problems on Large-Scale Graphs. Journal of Mathematical Sciences, 128 (6), 3487–3495. doi: 10.1007/s10958-005-0283-z
  12. Hrybkov, S., Oliinyk, H. (2015). Modeling of the decision support system structure in the planning and controlling of contracts implementation. Ukrainian Journal of Food Science, 3 (1), 123–130.
  13. Bass, L., Clements, P., Kazman, R. (2013). Software Architecture in Practice. Addison-Wesley Professional, 640.
  14. Niemeyer, P., Leuck, P. (2013). Learning Java. O'Reilly Media, 1010.
  15. Ritter, S. (2018). 4 Reasons Why Java is Still #1. Azul Systems. Available at: https://www.azul.com/4-reasons-java-still-1/
  16. Walls, C. (2018). Spring in Action. Manning publication, 500.
  17. Johnson, R., Hoeller, J. et. al. (2016). Spring Framework. Reference Documentation. Available at: https://docs.spring.io/spring/docs/4.3.9.RELEASE/spring-framework-reference/html/
  18. Oliinyk, H. V., Hrybkov, S. V. (2016). Pidtrymka mekhanizmu tranzaktsiyi prohramnoiu platformoiu Spring. Mizhnarodnoi naukovo-tekhnichnoi konferentsiyi «Suchasni metody, informatsiyne, prohramne ta tekhnichne zabezpechennia system upravlinnia orhanizatsiino-tekhnichnymy ta tekhnolohichnymy kompleksamy». Kyiv: NUKhT, 250–251.
  19. Moskalenko, N. V. (2017). Web-orientirovannaya informacionnaya sistema reklamnoy kompanii. Ekonomicheskie nauki, 61-1. Available at: https://novainfo.ru/article/?nid=11602
  20. Ahaev, A. V. (2012). WEB-orientirovannaya ekspertnaya sistema vybora programmnyh produktov. Nauka. Tekhnologii. Innovacii: materialy Vseros. nauch. konf. studentov, aspirantov i molodyh uchenyh. Novosibirsk. 263–266.
  21. Loboda, Yu. G., Orlova, O. Yu. (2014). Tekhnologii razrabotki Web-prilozheniy. Naukovi pratsi. Odesa: Odeska natsionalna akademiya kharchovykh tekhnolohiy, 46, 239–244.
  22. Mihalcea, М., Ebersole, S. et. al. Hibernate ORM 5.2.13.Final User Guide. Available at: https://docs.jboss.org/hibernate/orm/5.2/userguide/html_single/Hibernate_User_Guide.html
  23. Kalin, M. (2013). Java Web Services: Up and Running. O'Reilly Media, 360.
  24. OpenAPI Specification. Available at: https://swagger.io/specification/
  25. Smart, J. (2011). Jenkins: The Definitive Guide. O'Reilly Media, 404.

Downloads

Published

2018-05-30

How to Cite

Hrybkov, S., Oliinyk, H., & Litvinov, V. (2018). Web­oriented decision support system for planning agreements execution. Eastern-European Journal of Enterprise Technologies, 3(2 (93), 13–24. https://doi.org/10.15587/1729-4061.2018.132604