分布鲁棒机会约束优化问题的研究

doi:10.15960/j.cnki.issn.1007-6093.2020.01.009

摘要/Abstract

摘要： 机会约束作为求解随机优化问题的重要方法之一，在金融、工程、管理等领域均有着广泛的应用.随着实际问题呈现越来越复杂的不确定性状态，随机变量分布的准确信息难以预测，分布鲁棒机会约束作为有效求解随机变量信息模糊（不完备）下的随机优化问题被提出.近几年，研究者们不断提出分布鲁棒机会约束新的模型理论和算法.现总结了求解不同类型分布鲁棒机会约束问题的建模、模型求解、算法及应用的新进展.

关键词: 机会约束, 分布鲁棒优化, 算法

Abstract: As one of the most important models in stochastic problem, the chance constrained optimization problem has been widely used in the fields of finance, engineering, management and so on. As the practical problems become more and more complex, the probability distribution of the uncertainty is difficult to predict/estimate accurately. Distributionally robust chance constrained optimization problem, as an effective model with ambiguous distributional information about uncertainty, has been proposed in the literature. In recent years, researchers have constantly developed new models for distributionally robust chance constrained optimization problems. The main purpose of this paper is to review recent advances in emerging models for distributionally robust chance constrained optimization problems and their potential applications in practice.

Key words: chance constraints, distributionally robust optimization, algorithm

中图分类号:

O224

耿晓路, 童小娇. 分布鲁棒机会约束优化问题的研究[J]. 运筹学学报, 2020, 24(1): 115-130.

GENG Xiaolu, TONG Xiaojiao. A review on distributionally robust chance constrained optimization problems[J]. Operations Research Transactions, 2020, 24(1): 115-130.

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