{"title":"Fast solvers for nonsmooth optimization problems in phase separation","authors":"Pawan Kumar","doi":"10.15439/2015F366","DOIUrl":null,"url":null,"abstract":"The phase separation processes are typically modeled by well known Cahn-Hilliard equation with obstacle potential. Solving these equations correspond to a nonsmooth and nonlinear optimization problem. Recently a globally convergent Newton Schur method was proposed for the non-linear Schur complement corresponding to this 2 × 2 non-linear system. The proposed method is similar to an inexact active set method in the sense that the active sets are first identified by solving a quadratic obstacle problem corresponding to the (1, 1) block of the 2 × 2 system, and later solving a reduced linear system by annihilating the rows and columns corresponding to identified active sets. For solving the quadratic obstacle problem, various optimal multi-grid like methods have been proposed. However solving the reduced system remains a major bottleneck. In this paper, we explore an effective preconditioner for the reduced linear system that allows solving large scale optimization problem corresponding to Cahn-Hilliard and to possibly similar models.","PeriodicalId":276884,"journal":{"name":"2015 Federated Conference on Computer Science and Information Systems (FedCSIS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Federated Conference on Computer Science and Information Systems (FedCSIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15439/2015F366","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
The phase separation processes are typically modeled by well known Cahn-Hilliard equation with obstacle potential. Solving these equations correspond to a nonsmooth and nonlinear optimization problem. Recently a globally convergent Newton Schur method was proposed for the non-linear Schur complement corresponding to this 2 × 2 non-linear system. The proposed method is similar to an inexact active set method in the sense that the active sets are first identified by solving a quadratic obstacle problem corresponding to the (1, 1) block of the 2 × 2 system, and later solving a reduced linear system by annihilating the rows and columns corresponding to identified active sets. For solving the quadratic obstacle problem, various optimal multi-grid like methods have been proposed. However solving the reduced system remains a major bottleneck. In this paper, we explore an effective preconditioner for the reduced linear system that allows solving large scale optimization problem corresponding to Cahn-Hilliard and to possibly similar models.