Artificial Immune Principle Based Charging Optimization Algorithm for Refined Copper Strip Producing

With the purpose of optimize charging for refined copper strip producing, a multi-object real time charging model is established, in which some charging practical demand such as reusing copper resource, cutting down charging cost, reducing metal burn-up, substitutive degree among different brand old materials and so on are considered in detail. To resolve the model easily, it is converted and disposed. The immune principle is analyzed, the artificial immune principle based charging optimization algorithm (AIPCOA) is designed. Some key cycles including the representation method of antibody, the affinity between antibodies and the antigen as well as the affinity among the antibodies, the generating of initial population and so on are especially studied, and the detail implementing steps are given. To verify the validity of the algorithm, the algorithm is compared with the genetic algorithm (GA). The simulation result is verified that more diversity of the solution can be obtained by AIPCOA, more cross-sectional satisfaction solutions can be obtained by AIPCOA, thus, it is easy to selection the most adaptive scheme during practical charging. The artificial immune algorithm (AIA) is fit for solving the optimization problems in which several typical satisfaction solutions is demanded simultaneously as the optional schemes, and obvious practical operation flexibility and outstanding practical application outlook can be obtained by AIA.