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An Alternating Iteration Algorithm for a Parameter-Dependent Distributionally Robust Optimization Model
oleh: Shuang Lin, Jie Zhang, Nan Shi
Format: | Article |
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Diterbitkan: | MDPI AG 2022-04-01 |
Deskripsi
Based on a successive convex programming method, an alternating iteration algorithm is proposed for solving a parameter-dependent distributionally robust optimization. Under the Slater-type condition, the convergence analysis of the algorithm is obtained. When the objective function is convex, a modified algorithm is proposed and a less-conservative solution is obtained. Lastly, some numerical tests results are illustrated to show the efficiency of the algorithm.