BazEkon - Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie

BazEkon home page

Meny główne

Sapiecha Krzysztof (Cracow University of Technology, Poland), Ciopiński Leszek (Kielce University of Technology, Kielce, Poland), Deniziak Stanisław (Kielce University of Technology, Kielce, Poland)
An Application of Developmental Genetic Programming for Automatic Creation of Supervisors of Multi-task Real-Time Object-Oriented Systems
Annals of Computer Science and Information Systems, 2014, vol. 2, s. 501 - 509, rys., tab., bibliogr. 21 poz.
Słowa kluczowe
Algorytmy genetyczne, Modelowanie matematyczne, Optymalizacja
Genetic algorithms, Mathematical modeling, Optimalization
A concept of artificial supervisor of multi-task real-time object-oriented system is introduced. Next, a procedure for automatic creation of artificial supervisors is presented. The procedure is based on developmental genetic programming. As an input data, UML diagrams are used. A representative example of creation of a supervisor of building a house illustrates the procedure. The efficiency of the procedure from various points of view and comparison considerations are given.(original abstract)
Pełny tekst
  1. Alcaraz, J., & Maroto, C. (2001). A robust genetic algorithm for resource allocation in project scheduling. Annals of Operations Research, 102, 83-109.
  2. Binder R. V., Testing Object-Oriented Systems - Models, Patterns, and Tools, Addison-Wesley (1999)
  3. Blazewicz J., Lenstra J. K., Rinnooy Kan A. H. G., Scheduling subject to resource constraints: Classification and complexity, Discrete Applied Mathematics, No.5,1983, pp.11-24.
  4. Briand L. C., Labiche Y., A UML-Based Approach to System Testing, Software and Systems Modeling, vol. 1 (1), pp. 10-42, 2002.
  5. Deniziak S., Górski A., "Hardware/Software Co-Synthesis of Distributed Embedded Systems Using Genetic Programming", Lecture Notes in Computer Science, Springer-Verlag, 2008, pp.83-93.
  6. Gomaa H., Designing Concurrent, Distributed, and Real-Time Applications with UML. Addison-Wesley, 2000.
  7. Hartmann S., Briskorn D., A survey of variants and extensions of the resource-constrained project scheduling problem, European journal of operational research : EJOR. - Amsterdam : Elsevier, Vol. 207., 1 (16.11.), pp. 1-15 (2010).
  8. Hartmann, S. (1998). An competitive genetic algorithm for resourceconstrained project scheduling. Naval Research Logistics, 45(7), 733-750.;2-7
  9. Holland J. H., "Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology", Control, and Artificial Intelligence, University of Michigan Press, Ann Arbor, MI (reprinted 1992, MIT Press, Cambridge, MA).
  10. Jigorea R., Manolache S., Eles P., Zebo Peng, "Modelling of real-time embedded systems in an object-oriented design environment with UML," Proceedings. Third IEEE International Symposium on Object-Oriented Real-Time Distributed Computing, 2000, pp.210-213.
  11. Keller R. E., W.Banzhaf, "The evolution of genetic code in genetic programming", Proc. of the Genetic and Evolutionary Computation Conference, 1999, pp.1077-1082.
  12. Koza J. R., Poli R., "Genetic Programming", In Edmund Burke and Graham Kendal, editors. "Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques", Chapter 5. Springer, 2005.
  13. Koza, J., Bennett III , F. H., Andre, D., Keane, M. A., 1998. Evolutionary Design of Analog Electrical Circuits Using Genetic Programming. In: I. C. Parmee (ed.), Adaptive Computing in Design and Manufacture.
  14. Michalewicz Z., Genetic Algorithms + Data Structures = Evolution Programs, Springer-Verlag Berlin Heidelberg, 1996.
  15. Möhring R. H., Schulz A. S., Stork F., Uetz M., "Solving Project Scheduling Problems by Minimum Cut Computations", Management Science, v.49 n.3, pp.330-350, March 2003.
  16. Pasaje J. L. M., Harbour M. G., Drake J. M., "MAST Real-Time View: a graphic UML tool for modeling object-oriented real-time systems", In proceeding of: IEEE 22nd Real-Time Systems Symposium, 2001. (RTSS 2001).
  17. Pawiński G. and Sapiecha K., "Cost-efficient Project Management Based on Distributed Processing Model.", Proceedings of The 2013 21st Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, Belfast 2013
  18. Wei C., Liu P., Tsai Y., "Resource-constrained project management using enhanced theory of constraint", International Journal of Project Management, Vo. 20, No.7, 2002, pp.561-567.
  19. Wilson G., Heywood M., "Probabilistic Adaptive Mapping Developmental Genetic Programming (PAM DGP): A New Developmental Approach", Proceedings of the 9th International Conference on Parallel Problem Solving from Nature (PPSN IX), (Reykjavik 2007)
  20. Xiang Li, Lishan Kang, Wei Tan, "Optimized Research of Resource Constrained Project Scheduling Problem Based on Genetic Algorithms", Lecture Notes in Computer Science, Vol. 4683, 2007, pp 177-186. http: //
  21. Zoulfaghari H., Nematian J., Mahmoudi N., and Khodabandeh M.. 2013. A New Genetic Algorithm for the RCPSP in Large Scale. Int. J. Appl. Evol. Comput. 4, 2 (April 2013), 29-40.
Cytowane przez
Udostępnij na Facebooku Udostępnij na Twitterze Udostępnij na Google+ Udostępnij na Pinterest Udostępnij na LinkedIn Wyślij znajomemu