FAST-Fast Algorithm for the Scenario Technique

作     者：Care, Algo Garatti, Simone Campi, Marco C. 

作者机构：Univ Melbourne Dept Elect & Elect Engn Parkville Vic 3052 Australia Politecn Milan Dipartimento Elettron Informaz & Bioingn I-20133 Milan Italy Univ Brescia Dipartimento Ingn Informaz I-25123 Brescia Italy 

出 版 物：《OPERATIONS RESEARCH》 (运筹学)

年 卷 期：2014年第62卷第3期

页      面：662-671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] 

基　　金：Ministero dell'Istruzione, dell'Universita e della Ricerca (MIUR) European Union [FP7 257005] 

主　　题：stochastic programming chance-constrained optimization randomized algorithms sample-based methods scenario approach 

摘      要：The scenario approach is a recently introduced method to obtain feasible solutions to chance-constrained optimization problems based on random sampling. It has been noted that the sample complexity of the scenario approach rapidly increases with the number of optimization variables and this may pose a hurdle to its applicability to medium-and large-scale problems. We here introduce the Fast Algorithm for the Scenario Technique, a variant of the scenario optimization algorithm with reduced sample complexity.