Robust truss topology optimization via semidefinite programming with complementarity constraints: a difference-of-convex programming approach
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DOI: 10.1007/s10589-018-0013-3
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- Hunter D.R. & Lange K., 2004. "A Tutorial on MM Algorithms," The American Statistician, American Statistical Association, vol. 58, pages 30-37, February.
- Kenneth Lange & Eric C. Chi & Hua Zhou, 2014. "A Brief Survey of Modern Optimization for Statisticians," International Statistical Review, International Statistical Institute, vol. 82(1), pages 46-70, April.
- Le An & Pham Tao, 2005. "The DC (Difference of Convex Functions) Programming and DCA Revisited with DC Models of Real World Nonconvex Optimization Problems," Annals of Operations Research, Springer, vol. 133(1), pages 23-46, January.
- Amir Beck & Aharon Ben-Tal & Luba Tetruashvili, 2010. "A sequential parametric convex approximation method with applications to nonconvex truss topology design problems," Journal of Global Optimization, Springer, vol. 47(1), pages 29-51, May.
- Hoai Le Thi & Tao Pham Dinh, 2011. "On solving Linear Complementarity Problems by DC programming and DCA," Computational Optimization and Applications, Springer, vol. 50(3), pages 507-524, December.
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- Kerstin Dächert & Sauleh Siddiqui & Javier Saez-Gallego & Steven A. Gabriel & Juan Miguel Morales, 2019. "A Bicriteria Perspective on L-Penalty Approaches – a Corrigendum to Siddiqui and Gabriel’s L-Penalty Approach for Solving MPECs," Networks and Spatial Economics, Springer, vol. 19(4), pages 1199-1214, December.
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Keywords
Robust optimization; Design-dependent load; Complementarity constraint; Semidefinite programming; Difference-of-convex programming; Concave–convex procedure;All these keywords.
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