1. Proceedings
  2. I3M
  3. 2019
  4. EMSS
  5. 10.46354/i3m.2019.emss.035

Multi-objective optimization for a scheduling problem in the steel industry

  • a Viktoria A. Hauder  ,
  • b Andreas Beham  ,
  • c Sebastian Raggl  ,
  •  d Michael Affenzeller  
  • a,b,c,d Heuristic and Evolutionary Algorithms Laboratory, University of Applied Sciences Upper Austria, Hagenberg, Austria
  • a Institute for Production and Logistics Management, Johannes Kepler University Linz, Austria
  • b,d Institute for Formal Models and Verification, Johannes Kepler University Linz, Austria
Cite as
Hauder V.A., Beham A., Raggl S., Affenzeller M. (2019). Multi-objective optimization for a scheduling problem in the steel industry. Proceedings of the 31st European Modeling & Simulation Symposium (EMSS 2019), pp. 241-245. DOI: https://doi.org/10.46354/i3m.2019.emss.035.

Abstract

Multiple conflicting objectives such as costs versus quality are part of many optimization processes in the area of production and logistics management. Exactly such a case is also examined in this work. For an already existing resource-constrained project scheduling problem, a second objective function, inspired by the steel industry, is taken into account. Together with the presentation of the related mixed integer programming (MIP) and constraint programming (CP) models, the recently developed balanced box method (Boland, Charkhgard, and Savelsbergh 2015) is used to solve this bi-objective optimization problem. Both approaches (MIP and CP) are compared in terms of runtime and solution quality, showing the advantages of using CP.

References

  1. Aneja, Y.P. and Nair, K.P., 1979. Bicriteria transportation problem. Management Science, 25(1), pp.73-78.
  2. Bechikh, S., Datta, R. and Gupta, A. eds., 2016. Recent advances in evolutionary multi-objective optimization (Vol. 20). Springer.
  3. Bockmayr, A. and Hooker, J.N., 2005. Constraint programming. Handbooks in Operations Research and Management Science, 12, pp.559-600.
  4. Boland, N., Charkhgard, H. and Savelsbergh, M., 2015. A criterion space search algorithm for biobjective integer programming: The balanced box method. INFORMS Journal on Computing, 27(4), pp.735-754.
  5. Čapek, R., Šůcha, P. and Hanzálek, Z., 2012. Production scheduling with alternative process plans. European Journal of Operational Research, 217(2), pp.300-311.
  6. Deb, K., 2014. Multi-objective optimization. In Search methodologies (pp. 403-449). Springer, Boston, MA.
  7. Ehrgott, M., 2005. Multicriteria optimization (Vol. 491). Springer Science & Business Media.
  8. Haimes, Y.V., 1971. On a bicriterion formulation of the problems of integrated system identification and system optimization. IEEE transactions on systems, man, and cybernetics, 1(3), pp.296-297.
  9. Hamacher, H.W., Pedersen, C.R. and Ruzika, S., 2007. Finding representative systems for discrete bicriterion optimization problems. Operations Research Letters, 35(3), pp.336-344.
  10. Hartmann, S. and Briskorn, D., 2010. A survey of variants and extensions of the resource-constrained project scheduling problem. European Journal of operational research, 207(1), pp.1-14.
  11. Hauder, V.A., Beham A., Raggl S., Affenzeller M., 2018. Resource constrained project scheduling: a realworld extension for steel industry - Proceedings of the 30th European Modeling and Simulation Symposium EMSS2018, Budapest, Hungary.
  12. Hauder, V.A., Beham, A., Raggl, S., Parragh, S.N. and Affenzeller, M., 2019a. On constraint programming for a new flexible project scheduling problem with resource constraints. arXiv preprint arXiv:1902.09244.
  13. Hauder, V.A., Beham, A., Raggl, S. and Affenzeller, M., 2019b. Solving a flexible resource-constrained project scheduling problem under consideration of activity priorities. International Conference on Computer Aided Systems Theory. Accepted for Publication.
  14. Kellenbrink, C. and Helber, S., 2015. Scheduling resource-constrained projects with a flexible project structure. European Journal of Operational Research, 246(2), pp.379-391.
  15. Laborie, P., Rogerie, J., Shaw, P. and Vilím, P., 2018. IBM ILOG CP optimizer for scheduling. Constraints, 23(2), pp.210-250.
  16. Srinivas, N. and Deb, K., 1994. Multiobjective optimization using nondominated sorting in genetic algorithms. Evolutionary computation, 2(3), pp.221-248.
  17. Tao, S. and Dong, Z.S., 2017. Scheduling resource constrained project problem with alternative activity chains. Computers & Industrial Engineering, 114, pp.288-296.