刊物主题:Optimization; Operation Research/Decision Theory; Real Functions; Computer Science, general;
出版者:Springer US
ISSN:1573-2916
卷排序:67
文摘
Three feasibility sampling procedures are developed as add-on acceleration strategies in interval methods for solving global optimization problem over a bounded interval domain subject to one or two additional linear constraints. The main features of all three procedures are their abilities to quickly test any sub-domain’s feasibility and to actually locate a feasible point if the feasible set within the sub-domain is nonempty. This add-on feature of feasibility sampling can significantly lower upper bounds of the best objective function value in any interval method and improve its convergence and effectiveness.