Links

Publications

[34] S. Suzuki, Optimality conditions for quasiconvex programming in terms of quasiconjugate functions,

Minimax Theory Appl. to appear.

[33] H. Yasunaka and S. Suzuki, Quasiconjugate dual problems for quasiconvex programming,

Linear Nonlinear Anal. 9 (2023), 103-113. URL

[32] S. Suzuki, Subdifferential and optimality conditions for convex set functions,

Pure Appl. Funct. Anal. 8 (2023), 345-356. URL

[31] S. Suzuki, Conjugate dual problem for quasiconvex programming,

J. Nonlinear Convex Anal. 23 (2022), 879-889. URL

[30] S. Suzuki, ε-subdifferentials and related results for quasiconvex programming,

Linear Nonlinear Anal. 7 (2021), 185-197. URL

[29] S. Suzuki, Linear Programming Relaxation for Quasiconvex Programming,

J. Nonlinear Convex Anal. 22 (2021), 1251--1261. URL

[28] S. Suzuki, Karush-Kuhn-Tucker type optimality condition for quasiconvex programming in terms of Greenberg-Pierskalla subdifferential,

J. Global Optim. 79 (2021), 191--202. URL

[27] D. Kuroiwa, S. Suzuki and S. Yamamoto, Characterizations of the basic constraint qualification and its applications,

J. Nonlinear Anal. Optim. 11 (2020), 99--109. URL

[26] S. Suzuki and D. Kuroiwa, Duality theorems for convex and quasiconvex set functions,

SN Operations Research Forum, 1 (2020), 4 (13 pages). URL

[25] D. Kuroiwa, G. M. Lee, and S. Suzuki, Surrogate duality for optimization problems involving set functions,

Linear Nonlinear Anal. 5 (2019), 269--277. URL

[24] S. Suzuki, Optimality Conditions and Constraint Qualifications for Quasiconvex Programming,

J. Optim. Theory Appl. 183 (2019), 963--976. URL

[23] S. Suzuki and D. Kuroiwa, Sufficient conditions for well-posedness for quasiconvex programming,

J. Nonlinear Convex Anal. 19 (2018), 1711--1717. URL

[22] S. Suzuki and D. Kuroiwa, Fenchel duality for convex set functions,

Pure Appl. Funct. Anal. 3 (2018), 505--517. URL

[21] S. Suzuki and D. Kuroiwa, Surrogate duality for robust quasiconvex vector optimization,

Appl. Anal. Optim. 2 (2018), 27--39. URL

[20] S. Suzuki and D. Kuroiwa, Generators and constraint qualifications for quasiconvex inequality systems,

J. Nonlinear Convex Anal. 18 (2017), 2101--2121. URL

[19] S. Suzuki and D. Kuroiwa, Characterizations of the solution set for non-essentially quasiconvex programming,

Optim. Lett. 11 (2017), 1699--1712. URL

[18] S. Suzuki, Quasiconvexity of sum of quasiconvex functions,

Linear Nonlinear Anal. 3 (2017), 287--295. URL

[17] S. Suzuki, Duality theorems for quasiconvex programming with a reverse quasiconvex constraint,

Taiwanese J. Math. 21 (2017), 489--503. URL

[16] S. Suzuki and D. Kuroiwa, Duality Theorems for Separable Convex Programming without Qualifications,

J. Optim. Theory Appl. 172 (2017), 669--683. URL

[15] S. Suzuki and D. Kuroiwa, Nonlinear Error Bounds for Quasiconvex Inequality Systems,

Optim. Lett. 11 (2017), 107--120. URL

[14] S. Suzuki and D. Kuroiwa, A constraint qualification characterizing surrogate duality for quasiconvex programming,

Pac. J. Optim. 12 (2016), 87--100. URL

[13] S. Suzuki and D. Kuroiwa, Characterizations of the solution set for quasiconvex programming in terms of Greenberg-Pierskalla subdifferential,

J. Global Optim. 62 (2015), 431--441. URL

[12] S. Suzuki, D. Kuroiwa, and G. M. Lee, Surrogate duality for robust optimization,

European J. Oper. Res. 231 (2013), 257--262. URL

[11] S. Suzuki and D. Kuroiwa, Some constraint qualifications for quasiconvex vector-valued systems,

J. Global Optim. 55 (2013), 539--548. URL

[10] S. Suzuki, Quasiconvex duality theorems with quasiconjugates and generator,

Mem. Fac. Sci. Eng. Shimane Univ. Ser. B Math. Sci. 45 (2012), 1--39. URL

[9] S. Suzuki and D. Kuroiwa, Necessary and Sufficient Constraint Qualification for Surrogate Duality,

J. Optim. Theory Appl. 152 (2012), 366--377. URL

[8] S. Suzuki and D. Kuroiwa, Necessary and sufficient conditions for some constraint qualifications in quasiconvex programming,

Nonlinear Anal. 75 (2012), 2851--2858. URL

[7] Y. Saeki, S. Suzuki and D. Kuroiwa, A necessary and sufficient constraint qualification for DC programming problems with convex inequality constraints,

Scientiae Mathematicae Japonicae 74 (2011), 49--54. URL

[6] S. Suzuki and D. Kuroiwa, Subdifferential calculus for a quasiconvex function with generator,

J. Math. Anal. Appl. 384 (2011), 677--682. URL

[5] S. Suzuki and D. Kuroiwa, Sandwich theorem for quasiconvex functions and its applications,

J. Math. Anal. Appl. 379 (2011), 649--655. URL

[4] S. Suzuki and D. Kuroiwa, Optimality conditions and the basic constraint qualification for quasiconvex programming,

Nonlinear Anal. 74 (2011), 1279--1285. URL

[3] S. Suzuki and D. Kuroiwa, On set containment characterization and constraint qualification for quasiconvex programming,

J. Optim. Theory Appl. 149 (2011), 554--563. URL

[2] S. Suzuki, Set containment characterization with strict and weak quasiconvex inequalities,

J. Global Optim. 47 (2010), 273--285. URL

[1] S. Suzuki and D. Kuroiwa, Set containment characterization for quasiconvex programming,

J. Global Optim. 45 (2009), 551--563. URL

Proceedings

[10] S. Suzuki, Optimality conditions for quasiconvex programming with a reverse quasiconvex constraint,

Proceedings of the 10th Anniversary Conference on Nonlinear Analysis and Convex Analysis (2019), 303--310.

[9] S. Suzuki, D. Kuroiwa, and G. M. Lee, Surrogate duality for a certain class of uncertain problems,

Proceedings of the 8th International Conference on Nonlinear Analysis and Convex Analysis (2015), 447--455.

[8] S. Suzuki, Observations of constraint qualifications for quasiconvex programming,

Proceedings of the 3rd Asian Conference on Nonlinear Analysis and Optimization (2014), 319--329.

[7] S. Yamamoto, S. Suzuki and D. Kuroiwa, An observation of alternative theorem for separable convex functions,

Proceedings of the 7th International Conference on Nonlinear Analysis and Convex Analysis II (2013), 297--304.

[6] S. Suzuki and D. Kuroiwa, Observations of surrogate duality and its constraint qualifications for quasiconvex programming,

Proceedings of the 7th International Conference on Nonlinear Analysis and Convex Analysis II (2013), 215--221.

[5] Y. Saeki, S. Suzuki and D. Kuroiwa, A difference of convex and polyhedral convex functions programming problem,

Proceedings of the 7th International Conference on Nonlinear Analysis and Convex Analysis II (2013), 185--192.

[4] S. Suzuki and D. Kuroiwa, Observations of closed cone constraint qualification for quasiconvex programming,

Proceedings of the 6th International Conference on Nonlinear Analysis and Convex Analysis (2010), 321--326.

[3] S. Suzuki and D. Kuroiwa, Set containment characterization and mathematical programming,

Proceedings of the Fifth International Workshop on Computational Intelligence & Applications (2009), 264--266.

[2] S. Suzuki and D. Kuroiwa, Generalized characterizations on set containments for a certain class of quasiconvex functions,

Proceedings of the Asian Conference on Nonlinear Analysis and Optimization (2009), 331--338.

[1] S. Suzuki and D. Kuroiwa, A characterization of H-biquasiconjugate for quasiconvex functions,

Proceedings of the 5th International Conference on Nonlinear Analysis and Convex Analysis (2009), 193--199.

Others

[16] S. Suzuki, 準凸計画問題に対するKKT条件と制約想定,

非線形解析学と凸解析学の研究, 数理解析研究所講究録, 2190, (2021), 88--94.

[15] S. Suzuki and D. Kuroiwa, 準凸計画問題に対する劣微分を用いた最適性条件,

非線形解析学と凸解析学の研究, 数理解析研究所講究録 2112, (2019), 154--159.

[14] S. Suzuki and D. Kuroiwa, 準凸不等式系に対する非線形かつ大域的なerror boundに関する一考察,

非線形解析学と凸解析学の研究, 数理解析研究所講究録 2065, (2018), 30--38.

[13] S. Suzuki and D. Kuroiwa, 準凸計画問題に対する必要十分な最適性条件について,

非線形解析学と凸解析学の研究, 数理解析研究所講究録 2011, (2016), 166--171.

[12] 黒岩 大史, 鈴木 聡, 準凸解析と最適化理論,

数学, 68, (2016), 246--265.

[11] S. Suzuki and D. Kuroiwa, 準凸計画問題に対するsurrogate双対性と制約想定,

非線形解析学と凸解析学の研究, 数理解析研究所講究録 1963, (2015), 37--43.

[10] S. Suzuki, D. Kuroiwa, and G. M. Lee, 不確実性を持つ準凸計画問題に対するsurrogate双対定理,

非線形解析学と凸解析学の研究, 数理解析研究所講究録 1923, (2014), 214--220.

[9] S. Suzuki and D. Kuroiwa, 準凸計画問題に対する双対定理とその適用例,

非線形解析学と凸解析学の研究, 数理解析研究所講究録 1841, (2013), 86--92.

[8] S. Yamamoto, S. Suzuki and D. Kuroiwa, 分離可能凸関数における二者択一の定理,

非線形解析学と凸解析学の研究, 数理解析研究所講究録 1821, (2013), 257--262.

[7] S. Suzuki and D. Kuroiwa, 準凸関数に対する平均値の定理とその適用例,

非線形解析学と凸解析学の研究, 数理解析研究所講究録 1821, (2013), 239--244.

[6] S. Suzuki and D. Kuroiwa, 準凸関数に対するサンドイッチ定理とその適用例,

非線形解析学と凸解析学の研究, 数理解析研究所講究録 1755, (2011), 182--187.

[5] T. Shimomura, S. Suzuki and D. Kuroiwa, ベクトル値準凸制約をもつ最適化問題,

非線形解析学と凸解析学の研究, 数理解析研究所講究録 1685, (2010), 243--248.

[4] S. Suzuki and D. Kuroiwa, 準凸計画問題における制約想定とその適用例,

非線形解析学と凸解析学の研究, 数理解析研究所講究録 1685, (2010), 237--242.

[3] S. Suzuki and D. Kuroiwa, 集合の包含に関する一般化された結果とその適用例,

非線形解析学と凸解析学の研究, 数理解析研究所講究録 1643, (2009), 134--138.

[2] S. Suzuki and D. Kuroiwa, Characterizing set containments with quasiconvex inequalities,

非線形解析学と凸解析学の研究, 数理解析研究所講究録 1611, (2008), 56--60.

[1] S. Suzuki, M. Kurokawa and D. Kuroiwa, Observation on various conjugates of quasiconvex functions,

非線形解析学と凸解析学の研究, 数理解析研究所講究録 1544, (2007), 206--211.

Presentations

[44] S. Suzuki, 準凸計画問題に対するKKT最適性条件,

日本数学会2021年度秋季総合分科会, 千葉大学（オンライン開催）, 2021年9月17日.

[43] S. Suzuki, 準凸計画問題に対する最適性条件と制約想定,

日本数学会2021年度年会, 慶應義塾大学（オンライン開催）, 2021年3月16日.

[42] S. Suzuki, Optimality conditions and constraint qualifications for quasiconvex programming,

非線形解析学と凸解析学の研究, 京都大学数理解析研究所, 2019年9月3日.

[41] S. Suzuki, 準凸計画問題に対する劣微分を用いた最適性条件,

日本数学会2019年度年会, 東京工業大学, 2019年3月18日.

[40] S. Suzuki and D. Kuroiwa, Optimality conditions for quasiconvex programming in terms of subdifferentials,

非線形解析学と凸解析学の研究, 京都大学数理解析研究所, 2018年8月29日.

[39] S. Suzuki, 逆準凸制約を持つ準凸計画問題について,

日本数学会2018年度年会, 東京大学駒場キャンパス, 2018年3月19日.

[38] S. Suzuki, Quasiconvex programming with a reverse quasiconvex constraint,

The 10th Anniversary Conference on Nonlinear Analysis and Convex Analysis, Chitose Cultural Center, Hokkaido, Japan, July 5, 2017.

[37] S. Suzuki and D. Kuroiwa, Nonlinear error bounds in terms of generators of quasiconvex functions,

非線形解析学と凸解析学の研究, 京都大学数理解析研究所, 2016年8月31日.

[36] S. Suzuki and D. Kuroiwa, Surrogate duality for quasiconvex vector optimization with data uncertainty,

The fifth International Conference on Continuous Optimization, National Graduate Institute for Policy Studies, Tokyo, Japan, August 16, 2016.

[35] S. Suzuki and D. Kuroiwa, Nonlinear global error bounds for quasiconvex inequality systems,

The fifth Asian conference on Nonlinear Analysis and Optimization, Toki Messe, Niigata, Japan, August 2, 2016.

[34] S. Suzuki and D. Kuroiwa, 準凸計画問題における解集合の特徴付けについて,

日本数学会2015年度秋季総合分科会, 京都産業大学, 2015年9月16日.

[33] S. Suzuki and D. Kuroiwa, Necessary and sufficient optimality conditions for quasiconvex programming,

非線形解析学と凸解析学の研究, 京都大学数理解析研究所, 2015年9月9日.

[32] S. Suzuki, Optimality conditions and the solution set for quasiconvex programming,

Joint Workshop of Pukyong National University and Shimane University, Shimane University, Matsue, Shimane, Japan, August 21, 2015.

[31] S. Suzuki and D. Kuroiwa, Optimality conditions and characterizations of the solution set for quasiconvex programming,

International Workshop on Mathematical Sciences in Matsue, Shimane University, Matsue, Shimane, Japan, October 12, 2014.

[30] S. Suzuki and D. Kuroiwa, Surrogate双対性と制約想定について,

日本数学会2014年度秋季総合分科会, 広島大学, 2014年9月27日.

[29] S. Suzuki and D. Kuroiwa, On Surrogate Strong and Min-max Duality for Quasiconvex Programming,

非線形解析学と凸解析学の研究, 京都大学数理解析研究所, 2014年8月19日.

[28] S. Suzuki and D. Kuroiwa, A constraint qualification characterizing surrogate strong and min-max duality,

The Fourth Asian Conference on Nonlinear Analysis and Optimization, National Normal Taiwan University, Taipei, Taiwan, August 7, 2014.

[27] S. Suzuki and D. Kuroiwa, Surrogate duality for robust vector optimization,

The 9th International Conference on Optimization: Techniques and Applications, National Taiwan University of Science and Technology, Taipei, Taiwan, December 14, 2013.

[26] S. Suzuki, D. Kuroiwa, and G. M. Lee, Surrogate duality for quasiconvex programming under data uncertainty via robust optimization,

非線形解析学と凸解析学の研究, 京都大学数理解析研究所, 2013年10月11日.

[25] S. Suzuki and D. Kuroiwa, 不確実性を持つ準凸計画問題に対するsurrogate双対定理について,

日本数学会2013年度秋季総合分科会, 愛媛大学, 2013年9月25日.

[24] S. Suzuki, D. Kuroiwa and G. M. Lee, Surrogate duality and its constraint qualifications for robust quasiconvex optimization,

The Eighth international conference on Nonlinear Analysis and Convex Analysis, Hirosaki University, Hirosaki, Aomori, Japan, August 3, 2013.

[23] S. Suzuki and D. Kuroiwa, 準凸計画問題に対するLagrange型双対定理と生成集合について,

日本数学会2013年度年会, 京都大学, 2013年3月21日.

[22] S. Suzuki and D. Kuroiwa, 準凸計画問題に対するsurrogate双対定理について,

日本数学会2012年度秋季総合分科会, 九州大学, 2012年9月19日.

[21] S. Suzuki and D. Kuroiwa, Constraint qualifications for quasiconvex programming,

The Third Asian Conference on Nonlinear Analysis and Optimization, Kunibiki Messe, Matsue, Shimane, Japan, September 5, 2012.

[20] S. Suzuki and D. Kuroiwa, Duality theorems for quasiconvex programming,

非線形解析学と凸解析学の研究, 京都大学数理解析研究所, 2012年8月30日.

[19] S. Suzuki, 数理計画問題における最適性条件について,

2012年度松江セミナー, 島根大学, 2012年5月30日.

[18] S. Suzuki and D. Kuroiwa, 準凸関数に対する劣微分とその応用,

日本数学会2012年度年会, 東京理科大学神楽坂キャンパス, 2012年3月27日.

[17] S. Yamamoto, S. Suzuki and D. Kuroiwa, 分離可能凸関数の一考察,

非線形解析学と凸解析学の研究, 京都大学数理解析研究所, 2011年8月31日.

[16] S. Suzuki and D. Kuroiwa, 生成集合による準凸関数の平均値の定理,

非線形解析学と凸解析学の研究, 京都大学数理解析研究所, 2011年8月31日.

[15] S. Yamamoto, S. Suzuki and D. Kuroiwa, An alternative theorem for separable convex functions,

The 7th International Conference on Nonlinear Analysis and Convex Analysis, Pukyong National University, Busan, Republic of Korea, August 4, 2011.

[14] Y. Saeki, S. Suzuki and D. Kuroiwa, A qualification for nonlinear programming problems with convex inequality constraints,

The 7th International Conference on Nonlinear Analysis and Convex Analysis, Pukyong National University, Busan, Republic of Korea, August 4, 2011.

[13] S. Suzuki and D. Kuroiwa, Completely characterized constraint qualification for surrogate duality,

The 7th International Conference on Nonlinear Analysis and Convex Analysis, Pukyong National University, Busan, Republic of Korea, August 2, 2011.

[12] S. Suzuki and D. Kuroiwa, 準凸関数に対するサンドイッチ定理,

日本数学会2011年度年会, 早稲田大学, 2011年3月21日.

[11] S. Suzuki and D. Kuroiwa, 準凸関数に対するサンドイッチ定理について,

非線形解析学と凸解析学の研究, 京都大学数理解析研究所, 2010年9月1日.

[10] S. Suzuki and D. Kuroiwa, 準凸計画問題における最適性条件について,

日本数学会2010年度年会, 慶應義塾大学矢上キャンパス, 2010年3月26日.

[9] S. Suzuki and D. Kuroiwa, Set containment characterization and mathematical programming,

The fifth international workshop on Computational Intelligence & Applications, Hiroshima University, Hiroshima, Japan, November 11, 2009.

[8] T. Shimomura, S. Suzuki and D. Kuroiwa, ベクトル値準凸制約をもつ最適化問題,

非線形解析学と凸解析学の研究, 京都大学数理解析研究所, 2009年9月2日.

[7] S. Suzuki and D. Kuroiwa, 準凸計画問題に関するBasic Constraint Qualificationについて,

非線形解析学と凸解析学の研究, 京都大学数理解析研究所, 2009年9月2日.

[6] S. Suzuki and D. Kuroiwa, Closed cone constraint qualification for quasiconvex programming,

The Sixth International Conference on Nonlinear Analysis and Convex Analysis, Tokyo Institute of Technology, Tokyo, Japan, March 30, 2009.

[5] S. Suzuki and D. Kuroiwa, Generalized characterizations on set containments for quasiconvex programming,

Asian Conference on Nonlinear Analysis and Optimization, Kunibiki Messe, Matsue, Japan, September 16, 2008.

[4] S. Suzuki and D. Kuroiwa, Generalized Results on Set Containments with Quasiconvex Inequalities,

非線形解析学と凸解析学の研究, 京都大学数理解析研究所, 2008年9月2日.

[3] S. Suzuki and D. Kuroiwa, Characterizing set containments with quasiconvex inequalities,

非線形解析学と凸解析学の研究, 京都大学数理解析研究所, 2007年9月3日.

[2] S. Suzuki and D. Kuroiwa, Set Containment Characterization for Quasiconvex Programming,

The fifth international conference on nonlinear analysis and convex analysis, National Tsing-Hua University, Hsinchu, Taiwan, June 2, 2007.

[1] S. Suzuki, M. Kurokawa and D. Kuroiwa, Observation on various conjugates of quasiconvex functions,

非線形解析学と凸解析学の研究, 京都大学数理解析研究所, 2006年8月30日.

Last update: January 9, 2024