Scheduling of steelmakingcontinuous casting process using deflected surrogate Lagrangian relaxation approach and DC algorithm Abstract   This paper investigates a hybrid flowshop scheduling (HFS) problem in the steelmaking continuous casting (SCC) process. Firstly, a mathematical model is built for the SCC scheduling problem. By relaxing the machine capacity constraint, the SCC scheduling problem can be transformed into a DC (difference of convex functions) programming problem, which can solved by using DC algorithm. Under some reasonable assumptions, the convergence of the DC algorithm is analyzed. Secondly, we propose an effective and efficient deflected surrogate subgradient method with global convergence to solve the Lagrangian dual (LD) problem. Thirdly, a simple heuristic method is designed to obtain a feasible scheduling. Lastly, we report some computational experiments to demonstrate the effectiveness of the proposed surrogate subgradient method by comparing with other similar surrogate subgradient methods.

An Integrated TwoStage Optimization Method for JobShop Bottleneck Planning and Scheduling In many literatures, planning and scheduling problems have been considered separately. Furthermore, resource constraints for scheduling are not only relevant for equipment, but are also strongly affected by second resources and set up conversions. This paper derives how constraint programming enables problemdependent specialization and increases planning and scheduling efficiency. Constraint programing based scheduling involves multiresources capacity limit, demand fulfill, precedence, initialization, down activities and sequencedependent set up. Then, we improve this model to address on more complex problems by introducing a twostage optimization method to decrease the computational burden. Finally, computational results are demonstrated to show the efficiency of the proposed method for a real time large scale planning and scheduling problem.