An Effective Algorithm for Quadratic Optimization with Non-Convex Inhomogeneous Quadratic Constraints

• 作者: Kaiyao Lou
• 来源期刊: 理论数学进展(英文)
• 学科: 数学
• 关键词: NONCONVEX INHOMOGENEOUS QUADRATIC Constrained QUADRATIC Optimization SEMIDEFINITE Programming RELAXATION NP-HARD
• 年，卷（期）: 2017,（4）
• 页码范围: 314-323
• 页数: 10页
• 分类号: O1

摘要

This paper considers the NP (Non-deterministic Polynomial)-hard problem of finding a minimum value of a quadratic program (QP), subject to m non-convex inhomogeneous quadratic constraints. One effective algorithm is proposed to get a feasible solution based on the optimal solution of its semidefinite programming (SDP) relaxation problem.