Logo PTI
Polish Information Processing Society
Logo FedCSIS

Annals of Computer Science and Information Systems, Volume 11

Proceedings of the 2017 Federated Conference on Computer Science and Information Systems

A hybrid method forOptimization Scheduling Groups of Jobs

,

DOI: http://dx.doi.org/10.15439/2017F81

Citation: Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 11, pages 579–586 ()

Full text

Abstract. This study deals with modelling and optimization of handling jobs (orders) in groups. All jobs in a group should be delivered at the same time after processing. The authors present a novel hybrid method, which includes the modelling and optimization of the problem in the hybrid environment composed of MP (Mathematical Programming) and CLP (Constraint Logic Programming). Due to the large complexity of the optimization problem, dedicated heuristic is also proposed instead of MP. The paper also presents an author's model for optimization scheduling groups of jobs. The model has been implemented in several environments: Hybrid (CLP/MP), Hybrid (CLP, heuristic), MP and heuristic. The obtained results of numerical experiments confirm the high efficiency and usefulness of the hybrid approach to optimize such problems.

References

  1. F. Guerriero, G. Miglionico, F. Olivito, “Strategic and operational decisions in restaurant revenue management”, European Journal of Operational Research 237,2014, pp. 1119–1132.
  2. G.M. Thompson, “Optimizing restaurant table configuration: Specifying combinable tables”, Cornell Hotel and Restaurant Administration Quartely 44, 2003, pp. 53–60.
  3. W.C. Chiang, J.C.H Chen, X. Xu, “An overview of research on revenue management: Current issues and future research”, International Journal of Revenue Management 1,2007 pp.97–128.
  4. G.M. Thompson, “Restaurant profitability management, The evolution of restaurant revenue management”, Cornell Hospitality Quarterly, 51, 2010, pp. 308–322.
  5. I. Ribas, R. Leisten, JM. Framinan, “Review and classification of hybrid flow shop scheduling problems from a production system and a solutions procedure perspective”, Computer Operation Research , 37, 2010, pp. 1439–1454.
  6. B. Tadayon, N. Salmasi, “A two-criteria objective function flexible flowshop scheduling problem with machine eligibility constraint” The International Journal of Advanced Manufacturing Technology, 64(5-8), 2013, pp. 1001-1015.
  7. A. Vidotto, K.N. Brown, J.C Beck, “Managing Restaurant Tables using Constraints” Knowledge Based Systems, March, 20(2), 2007, pp. 160-169.
  8. K. Apt, M. Wallace, “Constraint Logic Programming using Eclipse”. Cambridge: Cambridge University Press, 2006.
  9. P. Sitek, J. Wikarek, “A hybrid framework for the modelling and optimisation of decision problems in sustainable supply chain management”, International Journal of Production Research, vol 53(21), 2015, pp 6611-6628, http://dx.doi.org/10.1080/00207543.2015.1005762
  10. P. Sitek, J. Wikarek, “A Hybrid Programming Framework for Modeling and Solving Constraint Satisfaction and Optimization Problems” Scientific Programming, vol. 2016, Article ID 5102616, 2016. http://dx.doi.org/10.1155/2016/5102616.
  11. P. Sitek, “A hybrid approach to the two-echelon capacitated vehicle routing problem (2E-CVRP)”, Advances in Intelligent Systems and Computing, 267, 2014, pp. 251–263, http://dx.doi.org/10.1007/978-3-319-05353-0_25
  12. J. Wikarek, :Implementation Aspects of Hybrid Solution Framework”, Recent Advancees in Automation, Robotics and Measuring Techniques vol 267, 2014, pp. 317-328. http://dx.doi.org/10.1007/978-3-319-05353-0_31
  13. G. Bocewicz, I. Nielsen, Z. Banaszak, “Iterative multimodal processes scheduling” Annual Reviews in Control 38(1), 2014, pp. 113-132
  14. M. Relich, “Knowledge acquisition for new product development with the use of an ERP database”, Proceedings of the Federated Conference on Computer Science and Information Systems, 2013, pp. 1285–1290.
  15. A. Schrijver, A. “Theory of Linear and Integer Programming”, John Wiley & Sons, New York, NY, USA 1998.
  16. G. Kłosowski, A. Gola, A. Świć, “Application of Fuzzy Logic in Assigning Workers to Production Tasks”, Omatu S., Selamat A., Bocewicz G., Sitek P., Nielsen I., Garcia-Garcia J.A., Bajo J. (eds.),  Distributed Computing  and Artificial Intelligence, 13th International Conference, Springer Series: Advances in Intelligent Systems and Computing, Vol. 474, 2016, pp. 505-513.
  17. G. Kłosowski, A. Gola. “Risk-based estimation of manufacturing order costs with artificial intelligence”, Ganzha M., Maciaszek L., Paprzycki M. (eds.), Proceedings of the 2016 Federated Conference on Computer Science and Information Systems (FEDCSIS), IEEE, 2016, pp. 729-732, http://dx.doi.org/10.15439/2016F323.