基于AIA的精铜板带生产原料选购优化  

Optimization of Raw Materials Selective Purchasing for Refined Copper Strip Producing by AIA

作　　者：常春光[1] 

机构地区：[1]沈阳建筑大学管理学院,沈阳110168

出　　处：《控制工程》2017年第12期2496-2501,共6页Control Engineering of China

基　　金：国家自然科学基金资助项目(51678375);辽宁省自然科学基金(2015020603)

摘　　要：为提高精铜板带生产原料选购的合理性,研究了人工免疫算法(Artifical Immune Algorithm,AIA)对其过程的优化方法。构建了精铜板带生产原料选购的多目标优化模型,充分考虑了原料库位的限制、待生产牌号配料的需要量与安全库存量、换牌号时洗炉对纯铜料的额外需求量、新购料与现有旧料间的比例关系、供应商供料能力约束、重点供应商与普通供应商的最低购料量等约束。进行模型求解前转化,设计了AIA算法的具体实现步骤。应用结果表明,通过AIA算法得到的解比利用PSO算法得到的解更具有显著的多样性。上述优化模型与AIA算法对于解决此类复杂优化问题的有效性。In order to promote the rationality of raw materials selective purchasing （RMSP） in refined copper strip producing, the optimization method for RMSP by artificial immune algorithm （AIA） is studied. A multi-objective optimization model is established. The constraints include limiting of inventory space, demand and safety inventory quantity of varied production brands, extra demand quantity of pure copper raw materials for brand exchanging or charges washing, ratio requirement between fresh purchasing raw materials and original ones, supplying capability limit of suppliers, the low limit for purchasing quantity of important and common suppliers. Then the model is converted, and the implement steps of AIA algorithm are designed in detail. Application results show that the diversity of solutions by AIA is more obvious than ones by PSO. The validity of the above optimization model and AIA algorithm for the complex problem such as RMSP in refined copper strip producing is validated.

关 键 词：人工免疫算法 亲和力 精铜板带 原料 选购 

分 类 号：TP278[自动化与计算机技术—检测技术与自动化装置]