Improving optimization using adaptive algorithms

Abstract In the research projects and industrial severe optimization problems can be met, where number of variables is high, there are a lot constraints, they highly nonlinear mostly discrete issues, running time calculated sometimes in weeks with usual methods on an average computer. most cases logistics industry, robust constraint time. The optimizations typical office configuration, company accepts suboptimal solution what method gives within appropriate limit. That is, why adaptivity needed. technique includes parameters fine-tuning. On this way, sensitive setting found. article, some additional adaptive for logistic have been investigated to increase effectivity, improve strict condition.