An improved evolutionary algorithm for complex-process optimization(IEACOP) is presented to achieve optimal
setting of load distribution about hot rolling mill. The algorithm is partially based on the principles of the scatter search,
which has flexible structure and is embedded in sub-methods that have search mechanism. Meanwhile, infinite folding
chaotic model and local search method are applied to improve initial population strategy and “go-beyond strategy” of indepth
search. Then the efficiency of the local optimal solution is improved. The experiment results show that IEACOP
makes use of fewer adjustable parameters to get feasible mathematical solution for the actual load distribution problems and
validate the real-time application, which is the organism including local search and global search.