Title: Coordination and Decomposition of ...
Publisher: Shaker Verlag Dez 2013
Publication Date: 2013
Book Condition: Neu
Neuware - Modern large-scale industrial production sites consist of many production areas each being subject to a variety of technical constraints. The general objective of planning and scheduling is to ensure the on-time delivery of the end product with the lowest possible consumption of resources. In the metal industry, the melt shop and the hot rolling mill represent about 90% of the entire steel production chain energy consumption. An adequate coordination between these two production areas can allow minimizing capital investment, space requirements and power consumption by keeping the storage of the intermediate products as low as possible. Traditionally, optimal schedules of the both production sections are determined separately using a combination of mathematical programming and heuristics. Therefore an optimal schedule of the whole production chain cannot be guaranteed. On the other hand, solving the complete problem for the combined production areas leads to a combinatorial explosion of the mixed-integer linear programming (MILP) model and makes the problem intractable. A bottom-up coordination heuristics of two large-scale flexible multi-stage batch (flow shop) scheduling problems is developed on the basis of an improved Bender's Decomposition Algorithm (Bender, 1962). An upper-level coordinator is formulated as an optimization problem based on the technical constraints of the bottleneck stages within the production sections. The obtained optimal solution of the coordinator is used as the coordination variables for the lowerlevel schedulers. The coordinator is iteratively updated using the feedback the lower-level schedulers information by adding integer and logical cuts. The location and number of bottleneck stages in the production sections might not be known a priori. An objective-oriented bottleneck definition for scheduling problems modeled as MILP is proposed. The bottleneck(s) are identified using a sensitivity analysis-based heuristics. The proposed coordination heuristics Shows improved results in terms of solution quality and computational effort when compared to other coordination approaches based on the Lagrangean Decomposition and the derivative-free optimization algorithms. The coordination heuristics is validated using actual production data collected from a steel plant. The obtained results showed a 7% increase of the total productivity, a 23% reduction of the slab yard inventory and a 9% reduction of the reheating furnace natural gas consumption when compared to an uncoordinated schedule, with no additional hardware investment. In summary, the proposed coordination approach is a general decomposition and coordination large-scale scheduling problems method that is able to systematically incorporate process knowledge. 186 pp. Englisch. Bookseller Inventory # 9783844024371
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