A deterministic algorithm for global optimizationстатья
Информация о цитировании статьи получена из
Web of Science,
Scopus
Статья опубликована в журнале из списка Web of Science и/или Scopus
Дата последнего поиска статьи во внешних источниках: 7 сентября 2018 г.
Аннотация:An algorithm for solving global optimization problems is developed. The objective and constraints are required to have gradients satisfying Lipschitz condition. The problem may contain both continuous and integer variables and the objective may be non-convex and multimodal. Improved lower bounds and new techniques to reduce the number of algorithm steps by employing the gradient information are proposed for unconstrained optimization. Computational testing on different test problems demonstrate the efficiency of the proposed method in comparison with the state of the art approaches.