Convex separable minimization subject to bounded variables

作     者：Stefanov, SM 

作者机构：Neofit Rilski Univ Dept Math Blagoevgrad Bulgaria 

出 版 物：《COMPUTATIONAL OPTIMIZATION AND APPLICATIONS》 (计算优化及其应用)

年 卷 期：2001年第18卷第1期

页      面：27-48页

核心收录：

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070104[理学-应用数学] 0701[理学-数学] 

主　　题：convex programming separable programming singly constrained program knapsack problem algorithms 

摘      要：A minimization problem with convex and separable objective function subject to a separable convex inequality constraint less than or equal to and bounded variables is considered. A necessary and sufficient condition is proved for a feasible solution to be an optimal solution to this problem. Convex minimization problems subject to linear equality/linear inequality greater than or equal to constraint, and bounds on the variables are also considered. A necessary and sufficient condition and a sufficient condition, respectively, are proved for a feasible solution to be an optimal solution to these two problems. Algorithms of polynomial complexity for solving the three problems are suggested and their convergence is proved. Some important forms of convex functions and computational results are given in the Appendix.