Semicertain relaxation in the design of the difficult systems
Abstract
The sensor network localization problem is solved with the help of semidefinite relaxation and generalized simplex method. Performing numerical experiments show the efficiency of proposed method.References
1. Overton M. Semidefinite Programming / M. Overton, H. Wolkowicz. — Mathematical Programming. — 1997. — No. 77.
— Р. 105—109.
2. Helmberg C. Semidefinite Programming For Combinatorial Optimization / C. Helmberg. — Berlin, 2000. — 150 p.
3. Freund R. M. Introduction to Semidefinite Programming / R. M. Freund. — Massachusett : Massachusetts Institute of
Technology, 2004. — 54 p.
4. Косолап А. І. Використання напіввизначеної оптимізації для моделювання складних систем / А. І. Косолап,
А. С. Перетятько // Математичні машини і системи. — 2012. — № 1. — С. 174—179.
5. Sum of Squares Method for Sensor Network Localization / Nie Jiawang. — University of Minnesota — 2006.
6. Spaseloc: An Adaptive Subproblem Algorithm For Scalable Wireless Sensor Network Localization / [W. Michael Carter,
H. Jin Holly, M. A. Saunders, Y. Ye]. — Siam J. Optim. — 2006. — Vol. 17, No. 4. — Р. 1102—1128.
7. Anderson B. D. O. Wireless sensor network localization techniques / B. D. O. Anderson, G. Mao, and B. Fidan // Computer
Networks, 2007. — No. 51. — Р. 2529—2553.
8. Biswas P. Semidefinite programming for ad hoc wireless sensor network localization / P. Biswas and Y. Ye // In Proceedings
of the 3-rd International Symposium on Information Processing in Sensor Networks, 2004. — Berkeley, CA, USA. —
P. 46—54.
9. Andrea Cassioli. Solving the Sensor Network Localization Problem using an Heuristic Multistage Approach / Andrea Cassioli.
— 2009.
10. Krislock N. Explicit Sensor Network Localization using Semidefinite Representations and Facial Reductions
/ N. Krislock, F. Wolkowicz. — Waterloo : University of Waterloo, 2010. — 35 p.
11. Man-Cho A. Theory of Semidefinite Programming for Sensor Network Localization / A. Man-Cho, Y. Ye. — ACMSIAM
Symposium on Descrete Algorithms, 2004. — 16 p.
12. SFSDP : a Sparse Version of Full Semidefinite Programming Relaxation for Sensor Network Localization Problems / [S.
Kim, M. Kojima, H. Waki, M. Yamashita]. — 2009. — 19 p.
13. Yamashita M. A High-Perfomance Software Package for Semidefinite Programs: SDPA 7 / M. Yamashita. — 2010. —
26 p.
14. Roumili H. Infeasible Interior Point Method for Semidefinite Programs / H. Roumili, A. Keraghel, A. Yassine // Applied
Mathematical Sciences. — 2007. — 10 p.
15. Косолап А. И. Обобщение симплекс-метода для решения задач полуопределенной оптимизации / А. И. Косолап //
Математичне та комп’ютерне моделювання. — 2010. — C. 99—106.
— Р. 105—109.
2. Helmberg C. Semidefinite Programming For Combinatorial Optimization / C. Helmberg. — Berlin, 2000. — 150 p.
3. Freund R. M. Introduction to Semidefinite Programming / R. M. Freund. — Massachusett : Massachusetts Institute of
Technology, 2004. — 54 p.
4. Косолап А. І. Використання напіввизначеної оптимізації для моделювання складних систем / А. І. Косолап,
А. С. Перетятько // Математичні машини і системи. — 2012. — № 1. — С. 174—179.
5. Sum of Squares Method for Sensor Network Localization / Nie Jiawang. — University of Minnesota — 2006.
6. Spaseloc: An Adaptive Subproblem Algorithm For Scalable Wireless Sensor Network Localization / [W. Michael Carter,
H. Jin Holly, M. A. Saunders, Y. Ye]. — Siam J. Optim. — 2006. — Vol. 17, No. 4. — Р. 1102—1128.
7. Anderson B. D. O. Wireless sensor network localization techniques / B. D. O. Anderson, G. Mao, and B. Fidan // Computer
Networks, 2007. — No. 51. — Р. 2529—2553.
8. Biswas P. Semidefinite programming for ad hoc wireless sensor network localization / P. Biswas and Y. Ye // In Proceedings
of the 3-rd International Symposium on Information Processing in Sensor Networks, 2004. — Berkeley, CA, USA. —
P. 46—54.
9. Andrea Cassioli. Solving the Sensor Network Localization Problem using an Heuristic Multistage Approach / Andrea Cassioli.
— 2009.
10. Krislock N. Explicit Sensor Network Localization using Semidefinite Representations and Facial Reductions
/ N. Krislock, F. Wolkowicz. — Waterloo : University of Waterloo, 2010. — 35 p.
11. Man-Cho A. Theory of Semidefinite Programming for Sensor Network Localization / A. Man-Cho, Y. Ye. — ACMSIAM
Symposium on Descrete Algorithms, 2004. — 16 p.
12. SFSDP : a Sparse Version of Full Semidefinite Programming Relaxation for Sensor Network Localization Problems / [S.
Kim, M. Kojima, H. Waki, M. Yamashita]. — 2009. — 19 p.
13. Yamashita M. A High-Perfomance Software Package for Semidefinite Programs: SDPA 7 / M. Yamashita. — 2010. —
26 p.
14. Roumili H. Infeasible Interior Point Method for Semidefinite Programs / H. Roumili, A. Keraghel, A. Yassine // Applied
Mathematical Sciences. — 2007. — 10 p.
15. Косолап А. И. Обобщение симплекс-метода для решения задач полуопределенной оптимизации / А. И. Косолап //
Математичне та комп’ютерне моделювання. — 2010. — C. 99—106.
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How to Cite
[1]
A. I. Kosolap and A. S. Peretiatko, “Semicertain relaxation in the design of the difficult systems”, Вісник ВПІ, no. 2, pp. 92–95, Apr. 2013.
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