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Knowledge based and CP-driven approach applied to multi product small-size production flow

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Języki publikacji
EN
Abstrakty
EN
Constraint Programming (CP) is an emergent software technology for declarative description and effective solving of large combinatorial problems, especially in the area of integrated production planning. In this context, CP can be considered an appropriate framework for development of decision making software, supporting scheduling of multi-robots in a multi-product job shop. The paper deals with the multi-resource problem, in which more than one shared renewable and non-renewable resource type may be required by a manufacturing operation and the availability of each type is time-windows limited. The problem is NP-complete. The aim of the paper is to present a knowledge based and CP-driven approach to multi-robot task allocation providing prompt service to a set of routine queries, stated both in direct and reverse way. Provided examples illustrate the cases with consideration of accurate and uncertain specification of robot and worker operation time.
Rocznik
Strony
69--95
Opis fizyczny
Bibliogr. 15 poz., rys.
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autor
autor
Bibliografia
  • BACH, I., BOCEWICZ, G. and BANASZAK, Z. (2008) Constraint programming approach to time-window and rnultiresource-constrained projects portfolio prototyping. In: N. T. Nguyen et al., eds., Industrial, Engineering mid Other Applications of Applied Intelligent Systems, IEA/AIE 2008. LNAI 5027, Springer-Verlag, Berlin-Heidelberg, 767-776.
  • BACH, I., BOCEWICZ, G. and BANASZAK, Z. (2009) Knowledge based and CLP-driven approach to multi product small-size production flow. Decision Making in Manufacturing and Services, 2 (1-2), 5-32.
  • BACH, I., MUSZYŃSKI, W. and BOCEWICZ, G. (2008) CP approach to project portfolio prototyping. In: New trends in data base management. WNT, Gliwice, 387-399.
  • BANASZAK, Z. (2006) CP-based decision support for project-driven manufacturing. In: J. Józefowska and J. Węglarz, eds., Perspectives in Modern Project Scheduling. International Series in Operations Research and Management Science, 92, Springer Verlag, New York, 409-437.
  • BANASZAK, Z., BOCEWICZ, G. and BACH, I. (2008) CP-driven Production Process Planning in Multiproject Environment. In: Decision Making in Manufacturing and Services 2 (1-2), 5-32.
  • BARTAK, R. (2004) Incomplete Depth-First Search Techniques: A Short Survey. In: J. Figwer, ed., Proc. 6th Workshop on Constraint Programming for Decision and Control, 7-14.
  • BOCEWICZ, G., BACH, I. and BANASZAK, Z. (2008) Decision support tool for project portfolio prototyping. Applied Computer Science (Performance evaluation models of manufacturing systems) 4 (2), 43-62.
  • BUBNICKI, Z. (1999) Learning processes and logic-algebraic method for the systems with knowledge representation. Systems analysis and management. Polish Academy of Sciences, Warsaw (in Polish).
  • CHANAS, S. and KOMBUROWSKI, J. (1981) The use of fuzzy variables in PERT. Fuzzy Sets and Systems, 5 (1), 11-19.
  • DUBOIS, D., FARGIER, H. and FORTEMPS, P. (2003) Fuzzy scheduling: Modeling flexible constraints vs. coping with incomplete knowledge. EJOR 147, 231-252.
  • LINDEROTH, T. and SAVELSBERGH, M.W.P. (1999) A computational study of search strategies in mixed integer programming. INFORMS Journal on Computing 11, 173-187.
  • PIEGAT, A. (1999) Fuzzy modelling and control. Exit, Warsaw (in Polish).
  • PUGET, J.F. (1994) A C+ 4 Implementations of CLP. Proceeding of SPICS 94.
  • SCHULTE, CH., SMOLKA, G. and WURTZ, J. (1998) Finite Domain Constraint Programming in Oz. DFKI OZ documentation series, German Research Center for Artificial Intelligence, Saarbruecken, Germany.
  • VAN HENTENRYCK, P. (1991) Constraint Logic Programming. Knowledge Engineering Review 6, 151-194.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAT5-0045-0022
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