Optimization of charge design with quality constraints based on particle swarm optimization
基于微粒群和满足质量约束的组炉方案优化方法

To deal with the market demand and the production organization feature of steel making enterprises, we formulate the optimization of charge design as a cluster analysis problem with quality constraints on chemical compositions. A particle-swarm-optimization-based(PSO-based) solution is proposed for reducing the dimensions based on the principal component analysis(PCA) techniques. The range constraints of chemical compositions for products with similar quality are introduced in terms of traditional process constraints, due time constraints and furnace capacity constraints, etc. The solution adopts an integration schema for charge plan and quality design. It performs the cluster analysis for candidate products with similar chemical compositions and constraints to realize the optimal charge design under quality constraints on steel products of multiple varieties and in small batch demands.