Modeling 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 for a steelmill becomes more flexible and complicated. The flexibility provides operators with auxiliary requirements through an implementable integrated production planning. In this paper, a mixed-integer nonlinear programming (MINLP) model is proposed for the optimal planning that incorporates various manufacturing constraints and flexibility in a steel plate mill. Furthermore, two solution strategies are developed to overcome the weakness in solving the MINLP problem directly. The first one is to transform the original MINLP formulation to an approximate mixed integer linear programming 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 instances are presented in terms of the effectiveness and applicability. The result shows that the second method performs better in computational efforts and solution accuracy. (C) 2015 The Chemical Industry and Engineering Society of China, and Chemical Industry Press. All rights reserved.

• Author: Shan Lu; Hongye Su; Charlotta Johnsson; Yue Wang; Lei Xie
• Department/s: Department of Automatic Control
• Publishing year: 2015
• Language: English
• Pages: 2037-2047
• Publication/Series: Chinese Journal of Chemical Engineering
• Volume: 23
• Issue: 12
• Links: http://dx.doi.org/10.1016/j.cjche.2015.10.003
• Document type: Journal article
• Publisher: Chemical Industry Press
• Topic: Production Engineering, Human Work Science and Ergonomics
• Keywords: Production planning; Steel plate mill; Flexibility; Mixed integer; nonlinear programming
• Status: Published
• ISBN/ISSN/Other: ISSN: 2210-321X