Multi-Stage Production Planning Modeling of Iron and Steel Enterprise Based on Genetic Algorithm

Abstract:

In accordance with the main flow characteristics of steel and iron production process, some problems are analyzed coming from the making, performance and feedback of the production planning of iron and steel business enterprises in this paper. By using operation research theories and genetic algorithms, one advanced planning model of iron and steel productions suitable of various circumstance and environments is established to set up on the factor of the segment and environment variety. Penalty function is adopted in the course of getting solution. These parameters of scale of father population, crossover probability, mutation probability and penalty factor are combined and optimized. At the same time, to improve these algorithms and the solution process actually, some optimized models and projects were put forward from some plans on the basis of collecting information. It accords with the actual conditions of this enterprise basically that the optimization solution to production plans of real iron and steel enterprise by using the algorithm.

• Periodical: Key Engineering Materials (Volumes 460-461)
• Pages: 540-545
• DOI: https://doi.org/10.4028/www.scientific.net/KEM.460-461.540
• Online since: January 2011
• Authors: Guo Zhang Jiang, Jian Yi Kong, Gong Fa Li, Liang Xi Xie
• Keywords: Advanced Production Planning, Genetic Algorithm (GA), MATLAB, Multi-Stage Planning Model, Steel Production

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