Iterative bundle-based decomposition for large-scale nonseparable convex optimization

作     者：Park, K Shin, YS 

作者机构：Hongik Univ Dept Ind Engn Mapo Ku Seoul 121791 South Korea 

出 版 物：《EUROPEAN JOURNAL OF OPERATIONAL RESEARCH》 (欧洲运筹学杂志)

年 卷 期：1998年第111卷第3期

页      面：598-616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 mathematical programming nonlinear programming optimization quadratic programming 

摘      要：There has been considerable research in solving large-scale separable convex optimization problems. In this paper we present an algorithm for large-scale nonseparable smooth convex optimization problems with block-angular linear constraints. The solution of the problem is approximated by solving a sequence of structured separable quadratic programs. The Bundle-based decomposition (BBD) method of Robinson (In: Prekopa, A., Szelezsan, J., Strazicky, B. (Eds.), System Modelling and Optimization, Springer, 1986, pp. 751-756;Annals de Institute Henri Poincare: Analyse Non Lineaire 6 (1989) 435-447) is applied to each separable quadratic program. We implement the algorithm and present computational experience. (C) 1998 Elsevier Science B.V. All rights reserved.