عنوان مقاله [English]
Production scheduling in the steel industry is a key component for productivity. It has been recognized as one of the most challengeable and complicated industrial scheduling problems. This research investigates the problem of steelmaking-continuous casting (SCC) multi objective scheduling as one of the most important units of steel industries. SCC is a high temperature and large scale logistics machining process with batch production at the last stage that identified as the key processes of modern iron and steel enterprises. This paper presents a mathematical model for scheduling this process based on actual production situations of technological constraints of SCC. According to the importance of on time delivery of products to the next unit (rolling) the objective considered two basic objective functions including 1) minimizing earliness and 2) minimizing lateness. The proposed model for this purpose is a nonlinear model. The model is converted to the mixed zero one linear model by some approaches that proposed in this paper. Model linearization help solve the model easier and faster. A solution methodology is developed in two-phase heuristic method. The first phase is a heuristic method based on branch and bound and the second phase is based on linear assignment technique. In the first phase a heuristic is presented at the beginning of the search in order to compute an initial upper bound. Proper branching schemes are developed and a method for reducing branches is established based upon the batch production in the continuous casting (CC) stage. The way of designing the algorithm according to the structure of proposed model of steelmaking-continuous casting, the initial upper bound, the method for reducing branches, proper branching schemes, and presenting a non- dominated solution are the features of the solution methodology. The computational experiments on randomly generated realistic problem indicate that the proposed algorithm with its features is capable of solving the proposed model quite efficiently.