Abstract
The primal-dual interior-point method is widely recognized as one of the most effective approaches for solving the linear complementarity problem. As an extension of the linear complementarity problem, the study of the weighted linear complementarity problem is more necessary. In this paper, a new full-Newton step primal-dual interior-point algorithm is proposed for the special weighted linear complementarity problem. At each iteration, the search directions of the method are determined via a positive-asymptotic kernel function. The iteration complexity of the algorithm is analyzed, and the result is the same as the currently best known complexity bound of the similar methods. Finally, the validity of the algorithm is verified by some numerical results.
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References
Asadi S, Darvay Z, Lesaja G, Amiri N, Potra F (2020) A full-Newton step interior-point method for monotone weighted linear complementarity problems. J Optim Theory App 186(115):864–878
Chi X, Wang G (2021) A full-Newton step infeasible interior-point method for the special weighted linear complementarity problem. J Optim Theory Appl 190:108–129
Chi X, Zhang R, Liu S (2021) A new full-Newton step feasible interior-point algorithm for linear weighted complementarity problem. Math Appl 34(2):304–311
Chi X, Yang Q, Wan Z, Zhang S (2023) The new full-Newton step interior-point algorithm for the Fisher market equilibrium problems based on a kernel function. J Ind Manag Optim 19(9):7018–7035
Darvay Z, Takacs P (2018) New method for determining search directions for interior-point algorithms in linear optimization. Optim Lett 12(5):1099–1116
Darvay Z, Papp I, Takacs P (2016) Complexity analysis of a full-newton step interior-point method for linear optimization. Per Math Hungarica 73(1):27–42
Geng J, Zhang M, Pang J (2020) A full-Newton step feasible IPM for semidefinite optimization based on a kernel function with linear growth term. Wuhan Univ J Nat Sci 134(6):30–38
Karmarkar N (1984) A new polynomial-time algorithm for linear programming. Combinatorica 4(4):373–395
Peng J, Roos C, Terlaky T (2002) Self-regular functions and new search directions for linear and semi-definite optimization. Math Program 93(1):129–171
Potra F (2012) Weighted complementarity problems-a new paradigm for computing equilibria. SIAM J Optim 2:1634–1654
Potra F (2016) Sufficient weighted complementarity problems. Comput Optim Appl 64(2):467–488
Roos C, Terlaky T, Vial J (1997) Theory and algorithms for linear optimization: an interior point approach. Wiley, Chichester
Roos C, Terlaky T, Vial J (2005) Interior point methods for linear optimization. Springer, New York
Takacs P, Darvay Z (2018) A primal-dual interior-point algorithm for symmetric optimization based on a new method for finding search directions. Optimization 67(6):889–905
Wang G, Bai Y (2009) A primal-dual interior-point algorithm for second-order cone optimization with full Nesterov-Todd step. Appl Math Comput 215(3):1047–1061
Wang G, Yu C, Teo K (2014) A full-Newton step feasible interior-point algorithm for \({P}_{*}(\kappa )\)-linear complementarity problems. J Global Optim 59(1):81–99
Yang Y (2020) Arc-search techniques for interior-point methods. CRC Press, Boca Raton
Zhang J (2016) A smoothing newton algorithm for weighted linear complementarity problem. Optim Lett 10:499–509
Zhang M, Huang K, Li M, Lv Y (2020) A new full-Newton step interior-point method for \({P}_{*}(\kappa )\)-LCP based on a positive-asymptotic kernel function. J Appl Math Comput 64:313–330
Zhang M, J G, Wu S (2021) A new infeasible interior-point algorithm with full-Newton steps for linear programming based on a kernel function. J Nonlinear Funct Anal 2021: 1–17
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DZ and JZ contributed to the primary writing of the manuscript. DZ and MZ were responsible for the proofs of the theorems and lemmas presented in the paper. The creation of Tables 1, 2 and 3 was the responsibility of Dechun Zhu. All authors participated in the review and approval of the final manuscript.
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Zhang, M., Zhu, D. & Zhong, J. A full-Newton step interior-point algorithm for the special weighted linear complementarity problem based on positive-asymptotic kernel function. Optim Eng (2023). https://doi.org/10.1007/s11081-023-09873-1
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DOI: https://doi.org/10.1007/s11081-023-09873-1
Keywords
- Full-Newton step
- Interior-point methods
- Weighted linear complementarity
- Positive-asymptotic kernel function