Abstract
With diversified requirements and varying manufacturing environments, the optimal production planning encountered in a steel mill has become more flexible and also complicated. The flexibility provides the operator with auxiliary options to satisfy customer 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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Number of pages | 13 |
Publication status | Published - 2014 |
Event | 25th Chinese Process Control Conference (CPCC2014) - Dalian, China Duration: 2014 Aug 9 → 2014 Sept 11 |
Conference
Conference | 25th Chinese Process Control Conference (CPCC2014) |
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Country/Territory | China |
City | Dalian |
Period | 2014/08/09 → 2014/09/11 |
Subject classification (UKÄ)
- Control Engineering
Free keywords
- mixed integer nonlinear programming
- flexibility
- steel plate mill
- production planning