Print Email Facebook Twitter Convergence of the mixing method Title Convergence of the mixing method: An iterative algorithm for solving diagonally constrained semidefinite programs Author Eelkema, Dominic (TU Delft Electrical Engineering, Mathematics and Computer Science) Contributor de Laat, D. (mentor) Degree granting institution Delft University of Technology Programme Applied Mathematics Date 2022-09-26 Abstract This thesis explores the convergence of the mixing method, an iter- ative algorithm for solving diagonally constrained semidefinite programs. In this paper we first give an exposition of the convergence proof for the mixing method based on the proof by Wang, Chang, and Kolter , where we restructure some parts of the proof and provide extra de- tails. Then we construct an example where the linear convergence rate of the mixing method is close to one when near the optimal solution. The mixing method is then compared for convergence speed to a semidefinite programming solver and gradient descent on random max-cut instances. For instances of the max-cut, it is found that the mixing method outper- forms other methods. Subject OptimizationSDPsemidefinite optimizationConvex To reference this document use: http://resolver.tudelft.nl/uuid:0a4435bb-8242-4f2d-af2c-e70ebc143ebe Part of collection Student theses Document type master thesis Rights © 2022 Dominic Eelkema Files PDF MCs_Thesis_DominicEelkema_final.pdf 614.3 KB Close viewer /islandora/object/uuid:0a4435bb-8242-4f2d-af2c-e70ebc143ebe/datastream/OBJ/view