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2011 | nr 206 Advanced Information Technologies for Management - AITM 2011: Inteligent Technologies and Applications | 108--119
Tytuł artykułu

Planning and Scheduling in Industrial Cluster with Combination of Expert System and Genetic Algorithm

Warianty tytułu
Planowanie i harmonogramowanie w klastrze przemysłowym z kombinacją systemu eksperckiego i algorytmu genetycznego
Języki publikacji
EN
Abstrakty
EN
In this paper, the author proposes an innovative method for planning and scheduling in industrial cluster called APRMC (Advanced Production Management in Cluster). The approach is implemented as a combination of expert system and genetic algorithm. The production planning problem is first solved, and then the scheduling problem is considered with the constraint of the solution. This research adopts the genetic algorithm developed by A. Ławrynowicz. (original abstract)
W referacie autorka proponuje innowacyjną metodę planowania i harmonogramowania w klastrze przemysłowym nazwaną APRMC (zaawansowane zarządzanie produkcją w klastrze). Podejście zostało zaimplementowane jako kombinacja systemu eksperckiego i algorytmu genetycznego. Pierwszy rozwiązywany jest problem planowania, a następnie harmonogramowania z uwzględnieniem ograniczeń rozwiązania. Badania adaptują algorytm genetyczny rozwijany przez A. Ławrynowicz. (abstrakt oryginalny)
Twórcy
  • Warsaw School of Economics, Poland
Bibliografia
  • Chan F.T.S., Chung S.H., Chan P.L.Y. (2005), An adaptive genetic algorithm with dominated genes for distributed scheduling problems, Expert System with Applications, Vol. 29, pp. 364-371.
  • Chen K.J., Ji P. (2007), A genetic algorithm for dynamic advanced planning and scheduling (DAPS) with frozen interval, Expert Systems with Applications, Vol. 33, pp. 1004-1010.
  • Chtourou H., Masmoudi W., Maalej A. (2005), An expert system for manufacturing systems machine selection, Expert Systems with Applications, Vol. 28, pp. 461-467.
  • Dayou L., Pu Y., Ji Y. (2009), Development of a multiobjective GA for advanced planning and scheduling problem, International Journal of Advanced Manufacturing Technology, Vol. 42, pp. 974-992.
  • Guldogan E.U. (2011), An integrated approach to machine selection and operation allocation problem, International Journal of Advanced Manufacturing Technology, Vol. 55, pp.797-805.
  • Huang H.C. (2009), Designing a knowledge-based system for strategic planning: A balanced scorecard perspective, Expert Systems with Applications, Vol. 36, pp. 209-218.
  • Jia H.Z., Fuh J.Y.H., Nee A.Y.C., Zhang Y.F. (2007), Integration of genetic algorithm and Gantt chart for job shop scheduling in distributed manufacturing systems, Computers & Industrial Engineering, Vol. 53, pp. 313-320.
  • Karacapilidis N., Adamides E., Evangelou C. (2006), A computerized knowledge management system for the manufacturing strategy process, Computers in Industry, Vol. 57, pp. 178-188.
  • Kobbacy K.A.H., Vadera S., Rasmy M.H. (2007), AI and OR in management of operations: History and trends, Journal of the Operational Research Society, Vol. 58, pp. 10-28.
  • López-Ortega O., López-Morales V., Villar-Medina I. (2008), Intelligent and collaborative Multi-Agent System to generate and schedule production orders, Journal of Intelligent Manufacturing, Vol. 19, pp. 677-687.
  • Ławrynowicz A. (2006), Hybrid approach with an expert system and a genetic algorithm to production management in the supply net, Intelligent Systems in Accounting, Finance and Management, Vol. 14, No. 1-2, pp. 59-76.
  • Ławrynowicz A. (2008), Integration of production planning and scheduling using an export system and a genetic algorithm, Journal of the Operational Research Society, Vol. 59, pp. 455-463.
  • Ławrynowicz A. (2009a), A new genetic algorithm for job shop scheduling in supply networks, [in:] K.A.H. Kobbacy, S. Vadera (Eds.), Proceedings of the Fourth European Conference on Intelligent Management Systems in Operations, University of Salford and The OR Society, Greater Manchester, pp. 101-110.
  • Ławrynowicz A. (2009b), A novel intelligent method for task scheduling in industrial cluster,[in:] J. Korczak, H. Dudycz, M. Dyczkowski (Eds.), Advanced Information Technologies for Management - AITM 2009, Research Papers of Wrocław University of Economics No. 85. Wrocław University of Economics, Wrocław 2009, pp. 170-178.
  • Ławrynowicz A. (2010a), A genetic algorithm for distributed scheduling in supply networks, [in:] M. Collan (Ed.), Proceedings of the 2nd Conference on Applied Operational Research - ICAOR'10, Turku, Finland. pp. 282-294.
  • Ławrynowicz A. (2010b), A novel intelligent method to support operations management in clusters, [in:] J. Korczak (Ed.), Data Mining and Business Intelligence, Research Papers of Wrocław University of Economics No. 85, Business Informatics 16,Wrocław University of Economics, Wrocław, pp. 148-165.
  • Ławrynowicz A. (2011), Advanced scheduling with genetic algorithms in supply networks, Journal of Manufacturing Technology Management, Vol. 22, No. 6, pp. 748-769.
  • Manzini R., Gamberi M., Gebennini E.. Regattieri A. (2008), An integrated approach to the design and management of a supply chain system, International Journal of Advanced Manufacturing Technology, Vol. 37, pp. 625-640.
  • Metaxiotis K.S., Askoums D., Psarras J. (2002), Expert system in production planning and scheduling. A state-of-the-art-survey, Journal of Intelligent Manufacturing, Vol. 13, pp. 253-260.
  • Morimoto T., Hatou K., Hashimoto Y. (1996), Intelligent control for a plant production system, Control Engineering in Practice, Vol. 4, No. 6, pp. 773-784.
  • Niu K.H. (2009), The involvement of firms in industrial clusters: A conceptual analysis, International Journal of Management, Vol. 26, No. 3, pp. 445-455.
  • Power Y., Bahri P.A. (2005), Integration techniques in intelligent operational management: A review, Knowledge-Based Systems, Vol. 18, pp. 89-97.
  • Tasan S.O., Tunali S. (2008), A review of the current applications of genetic algorithms in assembly line balancing, Journal of Intelligent Manufacturing, Vol. 19, pp. 49-69.
  • Wang Y.M, Yin H.L., Wang J. (2009), Genetic algorithm with new encoding scheme for job shop scheduling, International Journal of Advanced Manufacturing Technology, Vol. 44, pp. 977-984.
  • Welbank M. (1983), A Review of Knowledge Acquisition Techniques for Expert Systems, British Telecommunications Research Laboratories Technical Report, Ipswich, England.
  • Zobolas G.I., Tarantilis C.D. Ioannou G. (2009), A hybrid evolutionary algorithm for the job shop scheduling problem, Journal of the Operational Research Society, Vol. 60, No. 2, pp. 221-235.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171202613

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