Logo PTI
Polish Information Processing Society
Logo FedCSIS

Annals of Computer Science and Information Systems, Volume 8

Proceedings of the 2016 Federated Conference on Computer Science and Information Systems

A declarative decision support framework for scheduling groups of orders


DOI: http://dx.doi.org/10.15439/2016F38

Citation: Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 8, pages 733740 ()

Full text

Abstract. This paper deals with declarative decision support framework for scheduling groups of orders. All orders in a group should be delivered at the same time after processing. The authors present a novel declarative approach to modeling and solving scheduling problems as a declarative decision support framework. The proposed framework makes it possible to ask different types of questions (general, specific, logical, etc.). It also allows, scheduling emerging orders or groups of orders without changing the existing schedules. To implement was used CLP (Constraint Logic Programming) environment. To increase the efficiency of the framework, particularly in the area of optimization made its integration with MP (Mathematical Programming) environment. The paper also presents the implementation of illustrative model, using the proposed framework. In addition, an efficiency analysis of the presented solution in relation to the application of mathematical programming have been conducted.


  1. I. Ribas, R. Leisten, J.M. Framinan, “Review and classification of hybrid flow shop scheduling problems from a production system and a solutions procedure perspective“, in Computer Operation Research, 37, 2010, pp.1439–1454.
  2. B. Tadayon, N. Salmasi, N. “A two-criteria objective function flexible flowshop scheduling problem with machine eligibility constraint“ in The International Journal of Advanced Manufacturing Technology, 64(5-8), 2013, pp. 1001-1015.
  3. K. Apt, M. Wallace, Constraint Logic Programming using Eclipse. Cambridge: Cambridge University Press, 2006.
  4. G. Bocewicz, I. Nielsen, Z. Banaszak, “Iterative multimodal processes scheduling”, in Annual Reviews in Control, 38(1), 2014, pp. 113-132.
  5. F. Rossi, P. Van Beek, T. Walsh, Handbook of Constraint Programming, New York: Elsevier Sc. Inc, 2006.
  6. P. Sitek J. Wikarek, “A hybrid method for modeling and solving constrained search problems“, in Federated Conference on Computer Science and Information Systems (FedCSIS 2013), 2013, pp. 385-392
  7. P. Sitek, J. Wikarek, “Hybrid Solution Framework for Supply Chain Problems. “ in Distributed Computing and Artificial Intelligence (DCAI 2014), Book Series: Advances in Intelligent Systems and Computing, 290, 2014, pp. 11-18.
  8. P. Sitek, J. Wikarek “A hybrid framework for the modelling and optimisation of decision problems in sustainable supply chain management“, in International Journal of Production Research, 2015, pp. 6611-6628, http://dx.doi.org/10.1080/00207543.2015.1005762.
  9. P. Sitek, “A hybrid CP/MP approach to supply chain modelling, optimization and analysis“, in Federated Conference on Computer Science and Information Systems (FedCSIS), 2014, pp. 1345-1352, http://dx.doi.org/10.15439/2014F89
  10. P. Sitek, “A hybrid approach to the two-echelon capacitated vehicle routing problem (2E-CVRP) “, in Advances in Intelligent Systems and Computing, 267, 2014; pp.251–263, http://dx.doi.org/10.1007/978-3-319-05353-0_25.
  11. A. Schrijver, Theory of Linear and Integer Programming, John Wiley & Sons, New York, NY, USA, 1998.
  12. Eclipse, 2015, Eclipse - The Eclipse Foundation open source community website, Accessed August 12, http://www.eclipse.org.
  13. B.M.W. Cheng, K.M.F. Choi, J.H.M. Lee, J.C.K. Wu, “Increasing Constraint Propagation by Redundant Modeling: an Experience Report”, Constraints May 1999, Volume 4, Issue2, 1999, pp 167-192.
  14. M. Milano, M. Wallace M., “Integrating Operation Research in Constraint Programming”, in Annals of Operation Research, 175(1), 2010, pp. 37-76, http://dx.doi.org/10.1007/s10479-009-0654-9.
  15. P. Sitek, J. Wikarek, “A novel approach to decision support and optimization of group job handling for multimodal processes in manufacturing and services” in 15th IFAC/IEEE/IFIP/IFORS Symposium on Information Control Problems in Manufacturing, Ottawa, Kanada,2015, pp 2183-2188,http://dx.doi.org/10.1016/j.ifacol.2015.06.401
  16. P. Nielsen, I. Nielsen, K. Steger-Jensen, Analyzing and evaluating product demand interdependencies in Computers in Industry, 61 (9), 2010, 869-876, http://dx.doi.org/10.1016/j.compind.2010.07.012.
  17. M. Relich, W. Muszynski, The use of intelligent systems for planning and scheduling of product development projects in Procedia Computer Science, vol. 35, 2014, pp. 1586–1595.
  18. G. Kłosowski, A. Gola, A. Świć, Application of Fuzzy Logic Controler for Machine Load Balancing in Discrete Manufacturing System, [in:]. K. Jackowski et. al. (Eds.): IDEAL 2015, LNCS 9375, 2015, pp. 256-263.
  19. S. Bak, R. Czarnecki, S. Deniziak “Synthesis of Real-Time Cloud Applications for Internet of Things”, in Turkish Journal of Electrical Engineering &Computer Sciences, 2013, http://dx.doi.org/10.3906/elk-1302-178.