期刊
INTEGRATED COMPUTER-AIDED ENGINEERING
卷 29, 期 4, 页码 367-387出版社
IOS PRESS
DOI: 10.3233/ICA-220685
关键词
Flat steel production scheduling; hybrid approach; multi-objective mixed-integer linear programming; multi-agent systems; continuous flow model
类别
资金
- Research Fund for Coal and Steel (RFCS) of the European Union (EU) [847203]
The steel market competition is fierce, and profit can only be increased by lowering production and commercial costs. Attention is increasingly paid to production optimization through efficient scheduling strategies. Proper production scheduling can increase yield, maximize resource utilization, and minimize delays.
Nowadays the steel market is becoming ever more competitive for European steelworks, especially as far as flat steel products are concerned. As such competition determines the price products, profit can be increased only by lowering production and commercial costs. Production yield can be significantly increased through an appropriate scheduling of the semi-manufactured products among the available sub-processes, to ensure that customers' orders are timely completed, resources are optimally exploited, and delays are minimized. Therefore, an ever-increasing attention is paid toward production optimization through efficient scheduling strategies in the scientific and industrial communities. This paper proposes a hybrid approach to improve the flexibility of production scheduling in steelworks producing flat steel products. Such approach combines three methods holding different scopes and modelling different aspects: an auction-based multi-agent system is applied to face production uncertainties, multi-objective mixed-integer linear programming is used for global optimal scheduling of resources under steady conditions, while a continuous flow model copes with long-term production scheduling. According to the obtained simulation results, the integration and combination of these three approaches allow scheduling production in a flexible way by providing the capability to adapt to different production conditions.
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