FAST-Fast Algorithm for the Scenario Technique

• 成果类型: Article
• 署名作者: Care, Algo; Garatti, Simone; Campi, Marco C.
• 署名单位: University of Melbourne; Polytechnic University of Milan; University of Brescia
• 刊物名称: OPERATIONS RESEARCH
• ISSN/ISSBN: 0030-364X
• DOI: 10.1287/opre.2014.1257
• 发表日期: 2014
• 页码: 662-671
• 关键词: convex approximations; randomized solutions; Sample Complexity; robust solutions; DESIGN; optimization; feasibility; uncertainty; PROGRAMS

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.