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Research on QM-order Slabs Matching Problem and Load Allocation Problem in Hot Strip Mill

Author: LuoRui
Tutor: TangLiXin
School: Northeastern University
Course: Systems Engineering
Keywords: QM-order slabs matching clustering optimization load allocation differential evolution algorithm adaptive differential descent algorithm
CLC: TF089
Type: Master's thesis
Year: 2009
Downloads: 16
Quote: 0
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Abstract


Along with the progress of economic integration, steel enterprises, as one of the most essential parts for the economic development in our country, paly an important role in the national economic system. Nowadays, the increasing high product costs and low profit for steel enterprises are attributed to the rising price of the intenational raw materials. Steel enterprises, however, can no longer reduce the production costs via traditional methods. Therefore, a scientific and advanced method to regulate the production costs has been welcomed by steel enterprices during recent years.The main content for this dissertation, for the purpose of reducing the production costs in steel enterprises, are QM-order slabs matching problem and load allocation problem in hot strip finish rolling.(1) QM-order slabs matching problem.Being different from the common orders, QM-orders represent the marke-to-stock mode of production. Comparing to the open-order slabs matching problem, QM-order slabs matching problem have its distict characteristcs. At first, it requires the sales probability of all slabs in storage. Moreover, it needs to consider the storage level factors. At last, it asks to design the virtual contracts. After minutely studied the QM-order slabs matching problem, this dissertation proposes a method to calculate the sales probility of open-order slabs and another method to reckon the storage level for open-order slabs. This dissertaition also establishes a model to choose the hot-rolling plant for open-order slabs and another model to cluster these QM orders. Futhermore, this dissertation puts forward a heuristic-based optimization algorithm to cluster QM orders, which belongs to polynomial time algorithm. At last, based on the models and algorithm mentioned above, this dissertation developes a QM-order slabs matching decision support system, from which steel enterprises are able to get credibile and expedient decision supports.(2) Load allocation problem in hot strip finishing rolling.The load allocation problem in hot strip finish rolling comes from the idear to adapt to the recent trends in modern market, which grow toward to low-cost product. This idear is also a positive respsiveness to the national exhortation to build an economic society. After carefully analysed the charactics and the difficulties encounted in hot strip finishing rolling, this dissertation designs an optimization model to solve this problem. This model is based on the classic rolling theory, and reflects the typical characertstics of load allocation problem in hot strip finish rolling, such as its objective, subjects, and so on. In order to surmount some difficulties of this problem, such as the characteristics of high-order non-linear, continuous variables and the involute subjects, this dissertation uses differential evolution algorithm to solve this problem. This dissertation also proposes a decode-rule, which based on linear transformation, and a heuristic repair strategy, which based on linear transformation, to make differential evolution algorithm being suitable for this load allocation problem. Moreover, this dissertation designs an intelligent optimization algorithm based on differential evolution algorithm, adaptive differential descent algorithm, to obtain an effective computational result. This new algotithm adds an adaptive and increasing crossover probability strategy and a local search with disturbance strategy on the typical differential evolution algorithm. At last, this dissertation verifies the efficienty of those algorithms, by comparing these algorithms with the artificial algorithm based on the Know-how knowledge.

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CLC: > Industrial Technology > Metallurgical Industry > General issues > Metallurgical plant > Iron and steel enterprises
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