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Solutions of Nonconvex Quadratic Optimization Problems via Diagonalization
- Title
- Solutions of Nonconvex Quadratic Optimization Problems via Diagonalization
- Authors
- 유문숙
- Issue Date
- 2001
- Department/Major
- 대학원 수학과
- Keywords
- Nonconvex; Quadratic; Optimization; Problems; via Diagonalization
- Publisher
- The Graduate school of Ewha women university
- Degree
- Master
- Abstract
- SDP relaxation과 SOCP relaxation은 Nonconvex Quadratic Optimization Problem(QOP)의 근사해를 찾는다 특정 구조에서의 nonconvex QOP는 SDP와 SOCP에 의해 정확한 해를 찾을 수 있다. 따라서, 일반적인 QOP를 그 특정 구조의식으로 바꾸어, 더 정확한 해를 찾아낼 수 있는 방법을 제안하고, 수치적 실험 결과를 나열하여 제안된 본 방법의 이점을 보여준다.;Nonconvex Quadratic Optimization Problems (QOPs) are solved approximately by SDP (semidefinite programming) relaxation and SOCP (second-order-cone program) relaxation. Nonconvex QOPs with special structures can be solved exactly by SDP and SOCP. We propose a method to formulate general noncon- vex QOPs into the special form of the QOP, which can provide a way to find more accurate solutions. Numerical results are shown to illustrate advantages of the proposed method.
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