Abstract
In this paper, we introduce robust optimization and stochastic programming strategies for addressing demand uncertainty in steelmaking continuous casting operations. Robust optimization framework was first employed to develop a deterministic robust counterpart optimization model and to guarantee that the production schedule be feasible for the varying demands. Then, a two-stage scenario based stochastic programming framework was studied for the scheduling of steelmaking and continuous operations under demand uncertainty. To make the resulting stochastic programming problem computationally tractable, a scenario reduction method has been applied to reduce the number of scenarios to a small set of representative realizations. Results from both the robust optimization and stochastic programming methods demonstrate robustness under demand uncertainty and the robust solution is slightly better than the stochastic solution.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.