SDPNAL+ swMATH ID: 13239 Software Authors: Yang, Liuqin; Sun, Defeng; Toh, Kim-Chuan Description: SDPNAL+: a majorized semismooth Newton-CG augmented Lagrangian method for semidefinite programming with nonnegative constraints.In this paper, we present a majorized semismooth Newton-CG augmented Lagrangian method, called SDPNAL+, for semidefinite programming (SDP) with partial or full nonnegative constraints on the matrix variable. SDPNAL+ is a much enhanced version of SDPNAL introduced by X.-Y. Zhao et al. [SIAM J. Optim. 20, No. 4, 1737–1765 (2010; Zbl 1213.90175)] for solving generic SDPs. SDPNAL works very efficiently for nondegenerate SDPs but may encounter numerical difficulty for degenerate ones. Here we tackle this numerical difficulty by employing a majorized semismooth Newton-CG augmented Lagrangian method coupled with a convergent 3-block alternating direction method of multipliers introduced recently by D. Sun et al. [SIAM J. Optim. 25, No. 2, 882–915 (2015; Zbl 06444987)]. Numerical results for various large scale SDPs with or without nonnegative constraints show that the proposed method is not only fast but also robust in obtaining accurate solutions. It outperforms, by a significant margin, two other competitive publicly available first order methods based codes: (1) an alternating direction method of multipliers based solver called SDPAD by Z. Wen et al. [Math. Program. Comput. 2, No. 3–4, 203–230 (2010; Zbl 1206.90088)] and (2) a two-easy-block-decomposition hybrid proximal extragradient method called 2EBD-HPE by R. Monteiro et al. [“A first-order block-decomposition method for solving two-easy-block structured semidefinite programs”, Math. Program. Comput. 6, No. 2, 103–150 (2014; doi:10.1007/s12532-013-0062-7)]. In contrast to these two codes, we are able to solve all the 95 difficult SDP problems arising from the relaxations of quadratic assignment problems tested in SDPNAL to an accuracy of 10 -6 efficiently, while SDPAD and 2EBD-HPE successfully solve 30 and 16 problems, respectively. In addition, SDPNAL+ appears to be the only viable method currently available to solve large scale SDPs arising from rank-1 tensor approximation problems constructed by J. Nie and L. Wang [SIAM J. Matrix Anal. Appl. 35, No. 3, 1155–1179 (2014; Zbl 1305.65134)]. The largest rank-1 tensor approximation problem we solved (in about 14.5 h) is nonsym(21,4), in which its resulting SDP problem has matrix dimension n=9261 and the number of equality constraints m=12,326,390. Homepage: http://www.math.nus.edu.sg/~mattohkc/SDPNALplus.html Dependencies: Matlab Keywords: semidefinite programming; degeneracy; augmented Lagrangian; semismooth Newton-CG method Related Software: SDPT3; SeDuMi; QSDPNAL; QAPLIB; Mosek; SDPLR; DIMACS; Biq Mac; SDPA; GloptiPoly; SCS; BBCPOP; YALMIP; SDPNAL; Gurobi; UCI-ml; GitHub; BiqMac; 2EBD-HPE; QSDP Cited in: 78 Documents Standard Articles 2 Publications describing the Software, including 2 Publications in zbMATH Year SDPNAL+: A Matlab software for semidefinite programming with bound constraints (version 1.0). Zbl 1432.90104Sun, Defeng; Toh, Kim-Chuan; Yuan, Yancheng; Zhao, Xin-Yuan 2020 SDPNAL+: a majorized semismooth Newton-CG augmented Lagrangian method for semidefinite programming with nonnegative constraints. Zbl 1321.90085Yang, Liuqin; Sun, Defeng; Toh, Kim-Chuan 2015 all top 5 Cited by 135 Authors 22 Toh, Kim Chuan 16 Sun, Defeng 7 Kim, Sunyoung 6 Li, Xudong 5 Cui, Ying 5 Hu, ShengLong 5 Kojima, Masakazu 5 Zhao, Xinyuan 4 Chen, Liang 4 Ding, Chao 3 Liang, Ling 3 Ma, Shiqian 3 Sotirov, Renata 3 Tran Dinh Quoc 3 Wolkowicz, Henry 2 Cevher, Volkan 2 Chang, Xiaokai 2 Garcia, Joaquim Dias 2 Hu, Hao 2 Huang, Zheng-Hai 2 Ito, Naoki 2 Li, Qingna 2 Ling, Shuyang 2 Liu, Sanyang 2 Liu, Yafeng 2 Piccialli, Veronica 2 Sudoso, Antonio M. 2 Sun, Jie 2 Takeda, Akiko 2 Tropp, Joel A. 2 Udell, Madeleine 2 Wen, Zaiwen 2 Wiegele, Angelika 2 Yamashita, Makoto 2 Yang, Liuqin 2 Yuan, Yancheng 2 Yurtsever, Alp 2 Zheng, Mengmeng 1 Ahmadi, Amir Ali 1 Arima, Naohiko 1 Azuma, Godai 1 Bi, Shujun 1 Campos, Juan S. 1 Chen, Shixiang 1 Chen, Weikun 1 Chklovskii, Dmitri B. 1 de Meijer, Frank 1 Deng, Kangkang 1 Ding, Lijun 1 Ding, Mingcai 1 Dowson, Oscar 1 Eisenach, Carson 1 Fercoq, Olivier 1 Fukuda, Mituhiro 1 Gaar, Elisabeth 1 Ghasemi, Mehdi 1 Goulart, Paul J. 1 Graham, Naomi 1 Guo, Feng 1 Huang, Pengfei 1 Im, Jiyoung 1 Jiang, Zhuoxuan 1 Khoo, Yuehaw 1 Komeiji, Hikaru 1 Lasserre, Jean-Bernard 1 Legat, Benoît 1 Li, Guoyin 1 Li, Xiaodong 1 Li, Xinxin 1 Li, Yiyong 1 Li, Yongfeng 1 Lin, Tianyi 1 Lin, Youyicun 1 Liu, Han 1 Liu, Haoming 1 Liu, Haoyang 1 Liu, Xin 1 Liu, Yong-Jin 1 Lu, Shu 1 Lubin, Miles 1 Majumdar, Anirudha 1 Marshall, Murray Angus 1 Misener, Ruth 1 Mixon, Dustin G. 1 Nakatsukasa, Yuji 1 Narayanan, Vishnu 1 Oliveira, Danilo Elias 1 Pan, Shaohua 1 Pang, Jong-Shi 1 Parpas, Panos 1 Pataki, Gábor 1 Punnen, Abraham P. 1 Qi, Houduo 1 Qian, Yitian 1 Rauhut, Holger 1 Rendl, Franz 1 Rontsis, Nikitas 1 Russo Russo, Anna 1 Sarkar, Purnamrita 1 Saunderson, James ...and 35 more Authors all top 5 Cited in 27 Serials 11 Mathematical Programming. 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