Abstract
With diversified requirements and varying manufacturing environments, the optimal production planning encountered in a steel mill became more flexible and also complicated. The flexibility can provide the operators with auxiliary requirements through an implementable integrated production planning. In this paper, a mixed-integer nonlinear programming (MINLP) model is formulated for the optimal planning that incorporates various manufacturing constraints and the flexibility in a steel plate mill. Furthermore, two solution strategies are developed to overcome the weakness of solving MINLP problem directly. The first one is to transform the original MINLP formulation to an approximate mixed integer linear programming (MILP) using a classic linearization method. The second one is to decompose the original model using a branch-and-bound based iterative method. Computational experiments on various problem instances are presented in terms of the effectiveness and applicability. The result shows that the proposed second method performs better in computational efforts and solution accuracy.
Original language | English |
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Journal | Chinese Journal of Chemical Engineering |
Publication status | Published - 2015 |
Subject classification (UKÄ)
- Control Engineering
Free keywords
- mixed integer nonlinear programming
- flexibility
- steel plate mill
- production planning