Decision Support Tool for Group Job-shop Scheduling Problems

Yuri Mauergauz

Abstract

This paper presents a new tool for group job-shop scheduling problems. The tool encompasses a dynamic Pareto-optimal method based on two criteria simultaneously: relative setup expenditure criterion and average orders utility criterion. In this method the concept of production intensity as a dynamic production process parameter is used. The software used allows scheduling for medium quantity of jobs. The result of software application is the set of non-dominant versions proposed to a user for making a final choice. Based on this model, a decision support tool (DST) called OptJobShop is used for scheduling optimization. The decision support tool provides for scheduling simulation with various initial parameters, comparison of different scheduling versions and choice of the final decision.

References

  1. Barfod MB, Salling K.B. and Leleur S. (2011). Composite decision support by combining costbenefit and multi-criteria decision analysis. Decision Support Systems, 51(1), 167-175.
  2. Buehlmann, U., Ragsdale, C.T. and Gfeller, B. (2000). A spreadsheet-based decision support system for wood panel manufacturing. Decision Support Systems, 28(3), 207-227.
  3. Canon, L.-C. and Jeannot, E. (2011). MO-Greedy: an extended beam-search approach for solving a multicriteria scheduling problem on heterogeneous machines. IEEE International Symposium on Parallel and Distributed Processing Workshops and PhD Forum, 57-69.
  4. Garcia-Sabater, J.P. , Maheut, J. and Garcia-Sabater, J.J.(2009). A decision support system for aggregate production planning based on MILP: A case study from the automotive industry. In Proceedings of the International Conference on Computers & Industrial Engineering, 366-371, Troyes.
  5. Fonseca, D. J., Li, L. and Chen, D.-C. (2005). A decision support system for production planning in just-in-time manufacturing. Asian Journal of Information Technology, 4(6), 623-627.
  6. Hasan, S. M., Sarker, R. and Essam, D. (2012). A decision support system for solving job-shop scheduling problems using genetic algorithms. Flexible Services and Manufacturing Journal, 23(2), 137-155.
  7. Heilala J., Montonen J., Järvinen P., Kivikunnas S. (2010). Decision support using simulation for customer-driven nanufacturing system design and operations planning. In Decision Support Systems, Advances in, 235-260, Croatia, INTECH.
  8. Kalantari, M., Rabbani, M. and Ebadian,M. (2011). A decision support system for order acceptance/rejection in hybrid MRS/MTO production systems. Applied Mathematical Modelling, 35(3), 1363-1377.
  9. Kargin, A.A. and Mironenko, D. C. (2009). Concept and algorithm model of imitation and simulation for sheet cutting at primary operation shops of MZTM plant. Donetsk National University Herald, Series A, Natural sciences, 1, 452-457 (in Russian).
  10. Lee, W.J. and Lee, K.C. (1999). A meta decision support system approach to coordinating production/marketing decisions. Decision Support Systems, 25(3), 239-250.
  11. Mauergauz, Y. (2012). Objectives and constraints in advanced planning problems with regard to scale of production output and plan hierarchical level. International Journal of Industrial and Systems Engineering, 12(4), 369-393.
  12. Mauergauz, Y. (2013). Cost-efficiency method for production scheduling. In Proceedings of the World Congress on Engineering 2013, 587-593, London.
  13. Mahdavi, I., Shirazi, B. and Solimanpur, M. (2010). Development of a simulation-based decision support system for controlling stochastic flexible job shop manufacturing systems. Simulation Modelling Practice and Theory, 18, 768-786.
  14. Mansouri S.A, Gallear D. and Askariazad M. H. (2012). Decision support for build-to-order supply chain management through multiobjective optimization. International Journal of Production Economics 135(1), 24-36.
  15. Novak, D.C. and Ragsdale,C.T. (2003) A decision support methodology for stochastic multi-criteria linear programming using spread sheets. Decision Supports Systems. 36(1), 99-116.
  16. Nyhuis, P. and Wiendal, H.P. (2009). Fundamentals of Production Logistics. Springer, Berlin.
  17. Oguz,C., Salman,F.S. and Yalcin, Z.B. (2010) Order acceptance and scheduling decisions in make -toorder systems. International Journal of Production Economics, 125(1), 200-211.
  18. Okongwu, U., Lauras, M., Dupont, L. and Humez, V. (2012). A decision support system for optimising the order fulfillment process. Production Planning & Control, 23(8), 581-598.
  19. Ozdamar, L., Bozyel, M. A. and Birbil, S. I. (1998). A hierarchical decision support system for production planning (with case study). European Journal of Operational Research, 104(3), 403-422.
  20. Petrovic, D., Duenas, A. and Petrovic, S. (2007) Decision support tool for multi-objective jobshop scheduling problems with linguistically quantified decision functions. Decision Support Systems, 43(4), 1527-1538.
  21. Sakalli, U.S. and Birgoren, B. (2009). A spreadsheetbased decision support tool for blending problems in brass casting industry. Computers & Industrial Engineering, 56(2), 724-735.
  22. Silva,C.G., Figueira, J., Lisboa, J. and Barman, S. (2006). An interactive decision support system for an aggregate production planning model based on multiple criteria mixed integer linear programming. Omega, International Journal of Management Science, 34(2), 167-177.
  23. Silva,C. (2009). Combining ad hoc decision-making behaviour with formal planning and scheduling rules: a case study in the synthetic fibre production industry. Production Planning & Control, 20(7), 636 - 648.
  24. Silva Filho, O.S and Cezarino, W. (2007 ). Managerial decision support system for aggregate production plan generation. In Proceedings of the 19 International Conference on Production Research, Chile, Valparaiso, 1-6.
  25. Slotnik, S.A.(2011). Order acceptance and scheduling: a taxonomy and review. European Journal of Operational Research, 212(1), pages 1-11.
  26. Sotiris, G., Athanasios, S. and Ilias, T. (2008). A decision support system for detailed production scheduling in a Greek metal forming industry. Management of International Business and Economic Systems Transactions, 2(1), 41-59.
  27. Viviers, F. (1983). A decision support system for job shop scheduling. European Journal of Operational Research, 14(1), 95-103.
  28. Wang, J., Yang, J.Q. and Lee, H. (1994). Multicriteria order acceptance decision support in over-demanded job shops: a neural network approach. Mathematical Computer Modeling, 19(5), l-19.
Download


Paper Citation


in Harvard Style

Mauergauz Y. (2014). Decision Support Tool for Group Job-shop Scheduling Problems . In Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH, ISBN 978-989-758-038-3, pages 397-406. DOI: 10.5220/0004988903970406


in Bibtex Style

@conference{simultech14,
author={Yuri Mauergauz},
title={Decision Support Tool for Group Job-shop Scheduling Problems},
booktitle={Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,},
year={2014},
pages={397-406},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004988903970406},
isbn={978-989-758-038-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,
TI - Decision Support Tool for Group Job-shop Scheduling Problems
SN - 978-989-758-038-3
AU - Mauergauz Y.
PY - 2014
SP - 397
EP - 406
DO - 10.5220/0004988903970406