Second order sufficient conditions for a
class of bilevel programs with lower level second-order cone
programming problem

Xiaoni Chi; Zhongping Wan; Zijun Hao

doi:10.3934/jimo.2015.11.1111

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October 2015, 11(4): 1111-1125. doi: 10.3934/jimo.2015.11.1111

Second order sufficient conditions for a class of bilevel programs with lower level second-order cone programming problem

Xiaoni Chi ^1, , Zhongping Wan ^2, and Zijun Hao ^2,

1.	School of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin 541004, China
2.	School of Mathematics and Statistics, Wuhan University, Wuhan 430072, China, China

Received September 2012 Revised July 2014 Published March 2015

Abstract
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When there is uncertainty in the lower level optimization problem of a bilevel programming, it can be formulated by a robust optimization method as a bilevel program with lower level second-order cone programming problem (SOCBLP). In this paper, we show that the Lagrange multiplier set mapping of the lower level problem of a class of the SOCBLPs is upper semicontinuous under suitable assumptions. Based on this fact, we detect the similarities and relationships between the SOCBLP and its KKT reformulation. Then we derive the specific expression of the critical cone at a feasible point, and show that the second order sufficient conditions are sufficient for the second order growth at an M-stationary point of the SOCBLP under suitable conditions.

Keywords: critical cone, second order sufficient conditions., KKT reformulation, upper semicontinuity, Bilevel program with lower level second-order cone programming problem.

Mathematics Subject Classification: Primary: 90C30; Secondary: 90C4.

Citation: Xiaoni Chi, Zhongping Wan, Zijun Hao. Second order sufficient conditions for a class of bilevel programs with lower level second-order cone programming problem. Journal of Industrial & Management Optimization, 2015, 11 (4) : 1111-1125. doi: 10.3934/jimo.2015.11.1111

References:

[1]	F. Alizadeh and D. Goldfarb, Second-order cone Programming, Math. Program., 95 (2003), 3-51. doi: 10.1007/s10107-002-0339-5. Google Scholar
[2]	A. Ben-Tal, L. El Ghaoui and A. Nemirovski, Robust Optimization, Princeton University Press, Princeton, 2009. doi: 10.1515/9781400831050. Google Scholar
[3]	J. F. Bonnans and A. Shapiro, Perturbation Analysis of Optimization Problems, Springer, New York, 2000. doi: 10.1007/978-1-4612-1394-9. Google Scholar
[4]	X. J. Chen, Smoothing methods for complementarity problems and their applications: A survey, J. Oper. Res. Soc. Japan, 43 (2000), 32-47. doi: 10.1016/S0453-4514(00)88750-5. Google Scholar
[5]	X. -D. Chen, D. Sun and J. Sun, Complementarity functions and numerical experiments for second-order cone complementarity problems, Comput. Optim. Appl., 25 (2003), 39-56. doi: 10.1023/A:1022996819381. Google Scholar
[6]	X. J. Chen and S. H. Xiang, Computation of error bounds for P-matrix linear complementarity problems, Math. Program., Ser. A, 106 (2006), 513-525. doi: 10.1007/s10107-005-0645-9. Google Scholar
[7]	X. Chi, Z. Wan and Z. Hao, The models of bilevel programming with lower level second-order cone programs, J. Inequal. Appl., 2014 (2014), p168. doi: 10.1186/1029-242X-2014-168. Google Scholar
[8]	S. Dempe, Foundations of Bilevel Programming, Kluwer Academic Publishers, New York, 2002. Google Scholar
[9]	S. Dempe, Bilevel Optimization Problem: Existence of Optimal Solutions and Optimality Conditions, Report of CIMPA school, University of Delhi,, 2013., (). Google Scholar
[10]	S. Dempe and J. Dutta, Is bilevel programming a special case of a mathematical programming with complementarity constraints?, Math. Program., 131 (2012), 37-48. doi: 10.1007/s10107-010-0342-1. Google Scholar
[11]	C. Ding, D. Sun and J. Y. Ye, First order optimality conditions for mathematical programs with semidefinite cone complementarity constraints, Math. Program., Ser. A, 147 (2014), 539-579. doi: 10.1007/s10107-013-0735-z. Google Scholar
[12]	T. Ejiri, A Smoothing Method for Mathematical Programs with Second-Order Cone Complementarity Constraints, Master thesis, Kyoto University in Kyoto, 2007. Google Scholar
[13]	U. Faraut and A. Korányi, Analysis on Symmetric Cones, Oxford University Press, New York, 1994. Google Scholar
[14]	M. S. Gowda, R. Sznajder and J. Tao, Some P-properties for linear transformations on Euclidean Jordan algebras, Linear Algebra Appl., 393 (2004), 203-232. doi: 10.1016/j.laa.2004.03.028. Google Scholar
[15]	P. B. Hermanns and N. V. Thoai, Global optimization algorithm for solving bilevel programming problems with quadratic lower levels, J. Ind. Manag Optim., 6 (2010), 177-196. doi: 10.3934/jimo.2010.6.177. Google Scholar
[16]	Z. H. Huang and N. Lu, Global and global linear convergence of smoothing algorithm for the Cartesian $P_{}(\kappa)$-SCLCP, J. Ind. Manag Optim.,* 8 (2012), 67-86. doi: 10.3934/jimo.2012.8.67. Google Scholar
[17]	Y. Jiang, Optimization Problems with Second-Order Cone Equilibrium Constraints, (Chinese) Ph.D. thesis, Dalian University of Technology in Dalian, 2011. Google Scholar
[18]	H. Th. Jongen and G.-W. Weber, Nonlinear optimization: Characterization of structural optimization, J. Glob. Optim., 1 (1991), 47-64. doi: 10.1007/BF00120665. Google Scholar
[19]	M. Kojima, Strongly stable stationary solutions in nonlinear programs, in Analysis and Computation of Fixed Points (eds. S.M. Robinson), Academic Press, 43 (1980), 93-138. Google Scholar
[20]	Y. J. Kuo and H. D. Mittelmann, Interior point methods for second-order cone programming and OR applications, Comput. Optim. Appl., 28 (2004), 255-285. doi: 10.1023/B:COAP.0000033964.95511.23. Google Scholar
[21]	X. H. Liu and W. Z. Gu, Smoothing Newton algorithm based on a regularized one-parametric class of smoothing functions for generalized complementarity problems over symmetric cones, J. Ind. Manag Optim., 6 (2010), 363-380. doi: 10.3934/jimo.2010.6.363. Google Scholar
[22]	Y. Liu and L. Zhang, Convergence analysis of the augmented Lagrangian method for nonlinear second-order cone optimization problems, Nonlinear Anal., 67 (2007), 1359-1373. doi: 10.1016/j.na.2006.07.022. Google Scholar
[23]	M. S. Lobo, L. Vandenberghe, S. Boyd and H. Lebret, Applications of second-order cone programming, Linear Algebra Appl., 284 (1998), 193-228. doi: 10.1016/S0024-3795(98)10032-0. Google Scholar
[24]	B. S. Mordukhovich, Variational Analysis and Generalized Differentiation, vol.I : Basic Theory, Springer, Berlin, 2006. Google Scholar
[25]	J. V. Outrata and D. Sun, On the coderivative of the projection operator onto the second-order cone, Set-Valued Anal., 16 (2008), 999-1014. doi: 10.1007/s11228-008-0092-x. Google Scholar
[26]	R. T. Rockafellar and R. J. -B. Wets, Variational Analysis, Springer, Berlin, 1998. doi: 10.1007/978-3-642-02431-3. Google Scholar
[27]	J. Wu, L. Zhang and Y. Zhang, A smoothing Newton method for mathematical programs governed by second-order cone constrained generalized equations, J. Glob. Optim., 55 (2013), 359-385. doi: 10.1007/s10898-012-9880-9. Google Scholar
[28]	H. Yamamura, T. Okuno, S. Hayashi and M. Fukushima, A smoothing SQP method for mathematical programms with linear second-order cone complementarity constraints, Pac. J. Optim., 9 (2013), 345-372. Google Scholar
[29]	T. Yan and M. Fukushima, Smoothing method for mathematical programs with symmetric cone complementarity constraints, Optimization, 60 (2011), 113-128. doi: 10.1080/02331934.2010.541458. Google Scholar
[30]	Y. Zhang, L. Zhang and J. Wu, Convergence properties of a smoothing approach for mathematical programs with second-order cone complementarity constraints, Set-Valued Anal., 19 (2011), 609-646. doi: 10.1007/s11228-011-0190-z. Google Scholar

show all references

References:

[1]	F. Alizadeh and D. Goldfarb, Second-order cone Programming, Math. Program., 95 (2003), 3-51. doi: 10.1007/s10107-002-0339-5. Google Scholar
[2]	A. Ben-Tal, L. El Ghaoui and A. Nemirovski, Robust Optimization, Princeton University Press, Princeton, 2009. doi: 10.1515/9781400831050. Google Scholar
[3]	J. F. Bonnans and A. Shapiro, Perturbation Analysis of Optimization Problems, Springer, New York, 2000. doi: 10.1007/978-1-4612-1394-9. Google Scholar
[4]	X. J. Chen, Smoothing methods for complementarity problems and their applications: A survey, J. Oper. Res. Soc. Japan, 43 (2000), 32-47. doi: 10.1016/S0453-4514(00)88750-5. Google Scholar
[5]	X. -D. Chen, D. Sun and J. Sun, Complementarity functions and numerical experiments for second-order cone complementarity problems, Comput. Optim. Appl., 25 (2003), 39-56. doi: 10.1023/A:1022996819381. Google Scholar
[6]	X. J. Chen and S. H. Xiang, Computation of error bounds for P-matrix linear complementarity problems, Math. Program., Ser. A, 106 (2006), 513-525. doi: 10.1007/s10107-005-0645-9. Google Scholar
[7]	X. Chi, Z. Wan and Z. Hao, The models of bilevel programming with lower level second-order cone programs, J. Inequal. Appl., 2014 (2014), p168. doi: 10.1186/1029-242X-2014-168. Google Scholar
[8]	S. Dempe, Foundations of Bilevel Programming, Kluwer Academic Publishers, New York, 2002. Google Scholar
[9]	S. Dempe, Bilevel Optimization Problem: Existence of Optimal Solutions and Optimality Conditions, Report of CIMPA school, University of Delhi,, 2013., (). Google Scholar
[10]	S. Dempe and J. Dutta, Is bilevel programming a special case of a mathematical programming with complementarity constraints?, Math. Program., 131 (2012), 37-48. doi: 10.1007/s10107-010-0342-1. Google Scholar
[11]	C. Ding, D. Sun and J. Y. Ye, First order optimality conditions for mathematical programs with semidefinite cone complementarity constraints, Math. Program., Ser. A, 147 (2014), 539-579. doi: 10.1007/s10107-013-0735-z. Google Scholar
[12]	T. Ejiri, A Smoothing Method for Mathematical Programs with Second-Order Cone Complementarity Constraints, Master thesis, Kyoto University in Kyoto, 2007. Google Scholar
[13]	U. Faraut and A. Korányi, Analysis on Symmetric Cones, Oxford University Press, New York, 1994. Google Scholar
[14]	M. S. Gowda, R. Sznajder and J. Tao, Some P-properties for linear transformations on Euclidean Jordan algebras, Linear Algebra Appl., 393 (2004), 203-232. doi: 10.1016/j.laa.2004.03.028. Google Scholar
[15]	P. B. Hermanns and N. V. Thoai, Global optimization algorithm for solving bilevel programming problems with quadratic lower levels, J. Ind. Manag Optim., 6 (2010), 177-196. doi: 10.3934/jimo.2010.6.177. Google Scholar
[16]	Z. H. Huang and N. Lu, Global and global linear convergence of smoothing algorithm for the Cartesian $P_{}(\kappa)$-SCLCP, J. Ind. Manag Optim.,* 8 (2012), 67-86. doi: 10.3934/jimo.2012.8.67. Google Scholar
[17]	Y. Jiang, Optimization Problems with Second-Order Cone Equilibrium Constraints, (Chinese) Ph.D. thesis, Dalian University of Technology in Dalian, 2011. Google Scholar
[18]	H. Th. Jongen and G.-W. Weber, Nonlinear optimization: Characterization of structural optimization, J. Glob. Optim., 1 (1991), 47-64. doi: 10.1007/BF00120665. Google Scholar
[19]	M. Kojima, Strongly stable stationary solutions in nonlinear programs, in Analysis and Computation of Fixed Points (eds. S.M. Robinson), Academic Press, 43 (1980), 93-138. Google Scholar
[20]	Y. J. Kuo and H. D. Mittelmann, Interior point methods for second-order cone programming and OR applications, Comput. Optim. Appl., 28 (2004), 255-285. doi: 10.1023/B:COAP.0000033964.95511.23. Google Scholar
[21]	X. H. Liu and W. Z. Gu, Smoothing Newton algorithm based on a regularized one-parametric class of smoothing functions for generalized complementarity problems over symmetric cones, J. Ind. Manag Optim., 6 (2010), 363-380. doi: 10.3934/jimo.2010.6.363. Google Scholar
[22]	Y. Liu and L. Zhang, Convergence analysis of the augmented Lagrangian method for nonlinear second-order cone optimization problems, Nonlinear Anal., 67 (2007), 1359-1373. doi: 10.1016/j.na.2006.07.022. Google Scholar
[23]	M. S. Lobo, L. Vandenberghe, S. Boyd and H. Lebret, Applications of second-order cone programming, Linear Algebra Appl., 284 (1998), 193-228. doi: 10.1016/S0024-3795(98)10032-0. Google Scholar
[24]	B. S. Mordukhovich, Variational Analysis and Generalized Differentiation, vol.I : Basic Theory, Springer, Berlin, 2006. Google Scholar
[25]	J. V. Outrata and D. Sun, On the coderivative of the projection operator onto the second-order cone, Set-Valued Anal., 16 (2008), 999-1014. doi: 10.1007/s11228-008-0092-x. Google Scholar
[26]	R. T. Rockafellar and R. J. -B. Wets, Variational Analysis, Springer, Berlin, 1998. doi: 10.1007/978-3-642-02431-3. Google Scholar
[27]	J. Wu, L. Zhang and Y. Zhang, A smoothing Newton method for mathematical programs governed by second-order cone constrained generalized equations, J. Glob. Optim., 55 (2013), 359-385. doi: 10.1007/s10898-012-9880-9. Google Scholar
[28]	H. Yamamura, T. Okuno, S. Hayashi and M. Fukushima, A smoothing SQP method for mathematical programms with linear second-order cone complementarity constraints, Pac. J. Optim., 9 (2013), 345-372. Google Scholar
[29]	T. Yan and M. Fukushima, Smoothing method for mathematical programs with symmetric cone complementarity constraints, Optimization, 60 (2011), 113-128. doi: 10.1080/02331934.2010.541458. Google Scholar
[30]	Y. Zhang, L. Zhang and J. Wu, Convergence properties of a smoothing approach for mathematical programs with second-order cone complementarity constraints, Set-Valued Anal., 19 (2011), 609-646. doi: 10.1007/s11228-011-0190-z. Google Scholar

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Second order sufficient conditions for a class of bilevel programs with lower level second-order cone programming problem

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