基于人工免疫算法的精铜板带加工配料优化

Charging optimization for refined copper strip producing by artificial immune algorithm

为循环利用铜资源、降低成本、减少烧损,且满足不同牌号旧料可代用性等实际配料要求,建立了多目标实时配料模型,并进行模型转换,设计了精铜板带加工配料优化的人工免疫算法.重点研究了抗体表示、抗体与抗原及抗体与抗体亲和力的计算、初始种群产生等关键环节,给出了免疫算法的具体实现步骤.实验结果表明,与传统遗传算法相比,人工免疫算法可获得具有代表性的多个满意解,具有较强的多样性,便于在实际投料操作中选择.

A multi-objective real time model for charging optimization is established to reuse copper resource,cut down cost,reduce metal burn-up,and meet the demand of substitutive degree among different brand of old materials and so on,the model is converted,the artificial immune algorithm （AIA） based charging optimization algorithm for refined copper strip producing is designed. Some key cycles such as antibody representation,affinity calculation between antibodies and the antigen as well as that among the antibodies,initial population generating and so on are especially studied,and the detail implementing steps are given. The simulation result shows that,compared with the genetic algorithm （GA）,more cross-sectional satisfaction solutions with more diversity can be obtained by using AIA,thus,it is easy to select the most adaptive scheme during practical charging.