An Algorithm for Nonsymmetric Conic Optimization Inspired by MOSEK

Riley Badenbroek; Joachim Dahl

An Algorithm for Nonsymmetric Conic Optimization Inspired by MOSEK

Riley Badenbroek
, Joachim Dahl

Research output: Working paper › Other research output

193 Downloads (Pure)

Abstract

We analyze the scaling matrix, search direction, and neighborhood used in MOSEK's algorithm for nonsymmetric conic optimization [Dahl and Andersen, 2019]. It is proven that these can be used to compute a near-optimal solution to the homogeneous self-dual model in polynomial time.

Original language	English
Place of Publication	Ithaca
Publisher	Cornell University Library
Number of pages	29
Publication status	Submitted - Mar 2020

Publication series

Name	arXiv
Volume	2003.01546

Access to Document

2003.01546Submitted manuscript, 394 KB

https://arxiv.org/abs/2003.01546

Cite this

@techreport{bcf7ef05e4e64ce8b2e96d4e3beb3a84,

title = "An Algorithm for Nonsymmetric Conic Optimization Inspired by MOSEK",

abstract = "We analyze the scaling matrix, search direction, and neighborhood used in MOSEK's algorithm for nonsymmetric conic optimization [Dahl and Andersen, 2019]. It is proven that these can be used to compute a near-optimal solution to the homogeneous self-dual model in polynomial time.",

author = "Riley Badenbroek and Joachim Dahl",

year = "2020",

month = mar,

language = "English",

series = "arXiv",

publisher = "Cornell University Library",

type = "WorkingPaper",

institution = "Cornell University Library",

}

TY - UNPB

T1 - An Algorithm for Nonsymmetric Conic Optimization Inspired by MOSEK

AU - Badenbroek, Riley

AU - Dahl, Joachim

PY - 2020/3

Y1 - 2020/3

N2 - We analyze the scaling matrix, search direction, and neighborhood used in MOSEK's algorithm for nonsymmetric conic optimization [Dahl and Andersen, 2019]. It is proven that these can be used to compute a near-optimal solution to the homogeneous self-dual model in polynomial time.

AB - We analyze the scaling matrix, search direction, and neighborhood used in MOSEK's algorithm for nonsymmetric conic optimization [Dahl and Andersen, 2019]. It is proven that these can be used to compute a near-optimal solution to the homogeneous self-dual model in polynomial time.

M3 - Working paper

T3 - arXiv

BT - An Algorithm for Nonsymmetric Conic Optimization Inspired by MOSEK

PB - Cornell University Library

CY - Ithaca

ER -

An Algorithm for Nonsymmetric Conic Optimization Inspired by MOSEK

Abstract

Publication series

Access to Document

Fingerprint

Cite this