A New Robust Optimization Approach to Deal with Dependent Uncertain Parameters

被引：0

作者：

Mostofi, Amirhossein ^{[1
]}

Jian, Vipul ^{[1
]}

Momeni, Mojtaba Arab ^{[2
]}

机构：

[1] Victoria Univ Wellington, Sch Management, Wellington, New Zealand

[2] Iran Univ Sci & Technol, Dept Ind Engn, Tehran, Iran

来源：

2020 IEEE 7TH INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND APPLICATIONS (ICIEA 2020) | 2020年

关键词：

deterministic robust optimization; dependent uncertain parameters; consistence robust solution; primal and dual relations; MIN-MAX REGRET; CONVEX; ALGORITHM;

D O I：

10.1109/iciea49774.2020.9102070

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

In the optimization problems with uncertain parameters, a solution is said to be robust if it is feasible with high probability regarding the realization of uncertain parameters. In this paper, a new robust approach is developed for the linear problems in which the model parameters are dependent on each other. The proposed approach converts the linear model to an equivalent integer linear programming one using the primal and dual theorem. The results of the paper indicate the ability of the new approach in fixing some inconsistency of the common robust optimization approach for the mentioned problem.

引用

下载

页码：583 / 591

页数：9

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