An Effective Approach for the Scheduling of Steel-making and Continuous Casting System with Stochastic Processing Requirements

Abstract The steel-making and continuous casting system (SCCS) is the bottleneck in the iron and steel production, SCCS often involve various uncertainties such as the emergency customer orders, inaccurate estimate of ingredient components, the unpredictable machine breakdown or the inaccurate estimate of processing time. How to consider such uncertainties to build a better schedule in a limited time by a computationally efficient manner is becoming critical for the production of iron and steel. The stochastic dynamic programming method is adopt to solve the obtained subproblems which are relaxed by Lagrangian relaxation multipliers, a good dual solution is selected by using “ordinal optimization,” and the actual schedule is dynamically constructed based on the dual solution and the realization of random processing requirements. The method has been tested by using practical data from the Shanghai Bashan steel plant in China and could get near optimal solutions in a limited time; the stochastic processing requirements are effectively handled for the production.