Modelling and Optimization Methods of Integrated Production Planning for Steel Plate Mill with Flexible Customization

Summary, in English

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.

• Author: Shan Lu; Hongye Su; Charlotta Johnsson; Lie Xie
• Department/s: Department of Automatic Control
• Publishing year: 2014
• Language: English
• Document type: Conference paper
• Topic: Control Engineering
• Keywords: mixed integer nonlinear programming; flexibility; steel plate mill; production planning
• Conference name: 25th Chinese Process Control Conference (CPCC2014)
• Conference date: 2014-08-09 - 2014-09-11
• Conference place: Dalian, China
• Status: Published
• Research group: LCCC