# American Institute of Mathematical Sciences

January  2013, 9(1): 153-169. doi: 10.3934/jimo.2013.9.153

## Proximal point algorithm for nonlinear complementarity problem based on the generalized Fischer-Burmeister merit function

 1 Department of Mathematics, National Taiwan Normal University, Taipei 11677, Taiwan 2 School of Mathematical Sciences, Dalian University of Technology, Dalian 116024, China

Received  May 2011 Revised  May 2012 Published  December 2012

This paper is devoted to the study of the proximal point algorithm for solving monotone and nonmonotone nonlinear complementarity problems. The proximal point algorithm is to generate a sequence by solving subproblems that are regularizations of the original problem. After given an appropriate criterion for approximate solutions of subproblems by adopting a merit function, the proximal point algorithm is verified to have global and superlinear convergence properties. For the purpose of solving the subproblems efficiently, we introduce a generalized Newton method and show that only one Newton step is eventually needed to obtain a desired approximate solution that approximately satisfies the appropriate criterion under mild conditions. The motivations of this paper are twofold. One is analyzing the proximal point algorithm based on the generalized Fischer-Burmeister function which includes the Fischer-Burmeister function as special case, another one is trying to see if there are relativistic change on numerical performance when we adjust the parameter in the generalized Fischer-Burmeister.
Citation: Yu-Lin Chang, Jein-Shan Chen, Jia Wu. Proximal point algorithm for nonlinear complementarity problem based on the generalized Fischer-Burmeister merit function. Journal of Industrial & Management Optimization, 2013, 9 (1) : 153-169. doi: 10.3934/jimo.2013.9.153
##### References:
 [1] E. D. Andersen, C. Roos and T. Terlaky, On implementing a primal-dual interior-point method for conic quadratic optimization,, Mathematical Programming, 95 (2003), 249.  doi: 10.1007/s10107-002-0349-3.  Google Scholar [2] S. C. Billups, S. P. Dirkse and M. C. Soares, A comparison of algorithms for large scale mixed complementarity problems,, Computational Optimization and Applications, 7 (1997), 3.  doi: 10.1023/A:1008632215341.  Google Scholar [3] J.-S. Chen, The semismooth-related properties of a merit function and a descent method for the nonlinear complementarity problem,, Journal of Global Optimization, 36 (2006), 565.  doi: 10.1007/s10898-006-9027-y.  Google Scholar [4] J-.S. Chen, On some NCP-function based on the generalized Fischer-Burmeister function,, Asia-Pacific Journal of Operational Research, 24 (2007), 401.   Google Scholar [5] J.-S. Chen and S.-H. Pan, A family of NCP functions and a desent method for the nonlinear complementarity problem,, Computational Optimization and Applications, 40 (2008), 389.  doi: 10.1007/s10589-007-9086-0.  Google Scholar [6] J.-S. Chen and S.-H. Pan, A regularization semismooth Newton method based on the generalized Fischer-Burmeister function for $P_0$-NCPs,, Journal of Computational and Applied Mathematics, 220 (2008), 464.  doi: 10.1016/j.cam.2007.08.020.  Google Scholar [7] J.-S. Chen, H.-T. Gao and S.-H. Pan, An $R$-linearly convergent derivative-free algorithm for the NCPs based on the generalized Fischer-Burmeister merit function,, Journal of Computational and Applied Mathematics, 232 (2009), 455.  doi: 10.1016/j.cam.2009.06.022.  Google Scholar [8] J.-S. Chen, S.-H. Pan and C.-Y. Yang, Numerical comparison of two effective methods for mixed complementarity problems,, Journal of Computational and Applied Mathematics, 234 (2010), 667.  doi: 10.1016/j.cam.2010.01.004.  Google Scholar [9] X. Chen and H. Qi, Cartesian $P$-property and its applications to the semidefinite linear complementarity problem,, Mathematical Programming, 106 (2006), 177.  doi: 10.1007/s10107-005-0601-8.  Google Scholar [10] F. H. Clarke, "Optimization and Nonsmooth Analysis,", John Wiley and Sons, (1983).   Google Scholar [11] E. D. Dolan and J. J. More, Benchmarking optimization software with performance profiles,, Mathematical Programming, 91 (2002), 201.   Google Scholar [12] F. Facchinei, Structural and stability properties of $P_0$ nonlinear complementarity problems,, Mathematics of Operations Research, 23 (1998), 735.  doi: 10.1287/moor.23.3.735.  Google Scholar [13] F. Facchinei and C. Kanzow, Beyond monotonicity in regularization methods for nonlinear complementarity problems,, SIAM Journal on Control and Optimization, 37 (1999), 1150.  doi: 10.1137/S0363012997322935.  Google Scholar [14] F. Facchinei and J.-S. Pang, "Finite-Dimensional Variational Inequalities and Complementarity Problems,", Springer Verlag, (2003).   Google Scholar [15] F. Facchinei and J. Soares, A new merit function for nonlinear complementarity problems and a related algorithm,, SIAM Journal on Optimazation, 7 (1997), 225.  doi: 10.1137/S1052623494279110.  Google Scholar [16] M. C. Ferris and J.-S. Pang, Engineering and economic applications of complementarity problems,, SIAM J. Rev., 39 (1997), 669.  doi: 10.1137/S0036144595285963.  Google Scholar [17] A. Fischer, Solution of monotone complementarity problems with locally Lipschitzian functions,, Mathematical Programming, 76 (1997), 513.  doi: 10.1007/BF02614396.  Google Scholar [18] P. T. Harker and J.-S. Pang, Finite dimensional variational inequality and nonlinear complementarity problem: a survey of theory, algorithms and applications,, Mathematical Programming, 48 (1990), 161.  doi: 10.1007/BF01582255.  Google Scholar [19] Z.-H. Huang, The global linear and local quadratic convergence of a non-interior continuation algorithm for the LCP,, IMA J. Numer. Anal., 25 (2005), 670.  doi: 10.1093/imanum/dri008.  Google Scholar [20] Z.-H. Huang and W.-Z. Gu, A smoothing-type algorithm for solving linear complementarity problems with strong convergence properties,, Appl. Math. Optim., 57 (2008), 17.  doi: 10.1007/s00245-007-9004-y.  Google Scholar [21] Z.-H. Huang, L. Qi and D. Sun, Sub-quadratic convergence of a smoothing Newton algorithm for the $P_0$- and monotone LCP,, Mathematical Programming, 99 (2004), 423.  doi: 10.1007/s10107-003-0457-8.  Google Scholar [22] H.-Y. Jiang, M. Fukushima and L. Qietal., A trust region method for solving generalized complementarity problems,, SIAM Journal on Control and Optimization, 8 (1998), 140.  doi: 10.1137/S1052623495296541.  Google Scholar [23] C. Kanzow and H. Kleinmichel, A new class of semismooth Newton method for nonlinear complementarity problems,, Computational Optimization and Applications, 11 (1998), 227.  doi: 10.1023/A:1026424918464.  Google Scholar [24] C. Kanzow, N. Yamashita and M. Fukushima, New NCP-functions and their properties,, Journal of Optimization Theory and Applications, 94 (1997), 115.  doi: 10.1023/A:1022659603268.  Google Scholar [25] T. De Luca, F. Facchinei and C. Kanzow, A semismooth equation approach to the solution of nonlinear complementarity problems,, Mathematical Programming, 75 (1996), 407.  doi: 10.1007/BF02592192.  Google Scholar [26] F. J. Luque, Asymptotic convergence analysis of the proximal point algorithm,, SIAM Journal on Control and Optimization, 22 (1984), 277.  doi: 10.1137/0322019.  Google Scholar [27] B. Martinet, Perturbation des méthodes d'opimisation,, RAIRO Anal. Numér., 12 (1978), 153.   Google Scholar [28] R. Mifflin, Semismooth and semiconvex functions in constrained optimization,, SIAM Journal on Control and Optimization, 15 (1997), 957.   Google Scholar [29] J.-S. Pang, A posteriori error bounds for the linearly-constrained variational inequality problem,, Mathematics of Operations Research, 12 (1987), 474.  doi: 10.1287/moor.12.3.474.  Google Scholar [30] J.-S. Pang, Complementarity problems,, in, (1994), 271.   Google Scholar [31] J.-S. Pang and L. Qi, Nonsmooth equations: Motivation and algorithms,, SIAM Journal on Optimization, 3 (1993), 443.  doi: 10.1137/0803021.  Google Scholar [32] L. Qi, A convergence analysis of some algorithms for solving nonsmooth equations,, Mathematics of Operations Research, 18 (1993), 227.  doi: 10.1287/moor.18.1.227.  Google Scholar [33] L. Qi and J. Sun, A nonsmooth version of Newton's method,, Mathematical Programming, 58 (1993), 353.  doi: 10.1007/BF01581275.  Google Scholar [34] S. M. Robinson, Strongly regular generalized equations,, Mathematics of Operations Research, 5 (1980), 43.  doi: 10.1287/moor.5.1.43.  Google Scholar [35] R. T. Rockafellar, Monotone operators and the proximal point algorithm,, SIAM Journal on Control and Optimization, 14 (1976), 877.  doi: 10.1137/0314056.  Google Scholar [36] R. T. Rockafellar and R. J-B. Wets, "Variational Analysis,", Springer-Verlag Berlin Heidelberg, (1998).  doi: 10.1007/978-3-642-02431-3.  Google Scholar [37] D. Sun and L. Qi, On NCP-functions,, Computational Optimization and Applications, 13 (1999), 201.  doi: 10.1023/A:1008669226453.  Google Scholar [38] D. Sun and J. Sun, Strong semismoothness of the Fischer-Burmeister SDC and SOC complementarity functions,, Mathematical Programming, 103 (2005), 575.  doi: 10.1007/s10107-005-0577-4.  Google Scholar [39] J. Wu and J.-S. Chen, A proximal point algorithm for the monotone second-order cone complementarity problem,, Computational Optimization and Applications, 51 (2012), 1037.   Google Scholar [40] N. Yamashita and M. Fukushima, On stationary points of the implicitm Lagrangian for nonlinear complementarity problems,, Journal of Optimization Theory and Applications, 84 (1995), 653.  doi: 10.1007/BF02191990.  Google Scholar [41] N. Yamashita and M. Fukushima, Modified Newton methods for solving a semismooth reformulation of monotone complementarity problems,, Mathematical Programming, 76 (1997), 469.   Google Scholar [42] N. Yamashita and M. Fukushima, The proximal point algorithm with genuine superlinear convergence for the monotone complementarity problem,, SIAM Journal on Optimization, 11 (2000), 364.  doi: 10.1137/S105262349935949X.  Google Scholar [43] N. Yamashita, J. Imai and M. Fukushima, The proximal point algorithm for the $P_0$ complementarity problem,, in, (2001), 361.   Google Scholar

show all references

##### References:
 [1] E. D. Andersen, C. Roos and T. Terlaky, On implementing a primal-dual interior-point method for conic quadratic optimization,, Mathematical Programming, 95 (2003), 249.  doi: 10.1007/s10107-002-0349-3.  Google Scholar [2] S. C. Billups, S. P. Dirkse and M. C. Soares, A comparison of algorithms for large scale mixed complementarity problems,, Computational Optimization and Applications, 7 (1997), 3.  doi: 10.1023/A:1008632215341.  Google Scholar [3] J.-S. Chen, The semismooth-related properties of a merit function and a descent method for the nonlinear complementarity problem,, Journal of Global Optimization, 36 (2006), 565.  doi: 10.1007/s10898-006-9027-y.  Google Scholar [4] J-.S. Chen, On some NCP-function based on the generalized Fischer-Burmeister function,, Asia-Pacific Journal of Operational Research, 24 (2007), 401.   Google Scholar [5] J.-S. Chen and S.-H. Pan, A family of NCP functions and a desent method for the nonlinear complementarity problem,, Computational Optimization and Applications, 40 (2008), 389.  doi: 10.1007/s10589-007-9086-0.  Google Scholar [6] J.-S. Chen and S.-H. Pan, A regularization semismooth Newton method based on the generalized Fischer-Burmeister function for $P_0$-NCPs,, Journal of Computational and Applied Mathematics, 220 (2008), 464.  doi: 10.1016/j.cam.2007.08.020.  Google Scholar [7] J.-S. Chen, H.-T. Gao and S.-H. Pan, An $R$-linearly convergent derivative-free algorithm for the NCPs based on the generalized Fischer-Burmeister merit function,, Journal of Computational and Applied Mathematics, 232 (2009), 455.  doi: 10.1016/j.cam.2009.06.022.  Google Scholar [8] J.-S. Chen, S.-H. Pan and C.-Y. Yang, Numerical comparison of two effective methods for mixed complementarity problems,, Journal of Computational and Applied Mathematics, 234 (2010), 667.  doi: 10.1016/j.cam.2010.01.004.  Google Scholar [9] X. Chen and H. Qi, Cartesian $P$-property and its applications to the semidefinite linear complementarity problem,, Mathematical Programming, 106 (2006), 177.  doi: 10.1007/s10107-005-0601-8.  Google Scholar [10] F. H. Clarke, "Optimization and Nonsmooth Analysis,", John Wiley and Sons, (1983).   Google Scholar [11] E. D. Dolan and J. J. More, Benchmarking optimization software with performance profiles,, Mathematical Programming, 91 (2002), 201.   Google Scholar [12] F. Facchinei, Structural and stability properties of $P_0$ nonlinear complementarity problems,, Mathematics of Operations Research, 23 (1998), 735.  doi: 10.1287/moor.23.3.735.  Google Scholar [13] F. Facchinei and C. Kanzow, Beyond monotonicity in regularization methods for nonlinear complementarity problems,, SIAM Journal on Control and Optimization, 37 (1999), 1150.  doi: 10.1137/S0363012997322935.  Google Scholar [14] F. Facchinei and J.-S. Pang, "Finite-Dimensional Variational Inequalities and Complementarity Problems,", Springer Verlag, (2003).   Google Scholar [15] F. Facchinei and J. Soares, A new merit function for nonlinear complementarity problems and a related algorithm,, SIAM Journal on Optimazation, 7 (1997), 225.  doi: 10.1137/S1052623494279110.  Google Scholar [16] M. C. Ferris and J.-S. Pang, Engineering and economic applications of complementarity problems,, SIAM J. Rev., 39 (1997), 669.  doi: 10.1137/S0036144595285963.  Google Scholar [17] A. Fischer, Solution of monotone complementarity problems with locally Lipschitzian functions,, Mathematical Programming, 76 (1997), 513.  doi: 10.1007/BF02614396.  Google Scholar [18] P. T. Harker and J.-S. Pang, Finite dimensional variational inequality and nonlinear complementarity problem: a survey of theory, algorithms and applications,, Mathematical Programming, 48 (1990), 161.  doi: 10.1007/BF01582255.  Google Scholar [19] Z.-H. Huang, The global linear and local quadratic convergence of a non-interior continuation algorithm for the LCP,, IMA J. Numer. Anal., 25 (2005), 670.  doi: 10.1093/imanum/dri008.  Google Scholar [20] Z.-H. Huang and W.-Z. Gu, A smoothing-type algorithm for solving linear complementarity problems with strong convergence properties,, Appl. Math. Optim., 57 (2008), 17.  doi: 10.1007/s00245-007-9004-y.  Google Scholar [21] Z.-H. Huang, L. Qi and D. Sun, Sub-quadratic convergence of a smoothing Newton algorithm for the $P_0$- and monotone LCP,, Mathematical Programming, 99 (2004), 423.  doi: 10.1007/s10107-003-0457-8.  Google Scholar [22] H.-Y. Jiang, M. Fukushima and L. Qietal., A trust region method for solving generalized complementarity problems,, SIAM Journal on Control and Optimization, 8 (1998), 140.  doi: 10.1137/S1052623495296541.  Google Scholar [23] C. Kanzow and H. Kleinmichel, A new class of semismooth Newton method for nonlinear complementarity problems,, Computational Optimization and Applications, 11 (1998), 227.  doi: 10.1023/A:1026424918464.  Google Scholar [24] C. Kanzow, N. Yamashita and M. Fukushima, New NCP-functions and their properties,, Journal of Optimization Theory and Applications, 94 (1997), 115.  doi: 10.1023/A:1022659603268.  Google Scholar [25] T. De Luca, F. Facchinei and C. Kanzow, A semismooth equation approach to the solution of nonlinear complementarity problems,, Mathematical Programming, 75 (1996), 407.  doi: 10.1007/BF02592192.  Google Scholar [26] F. J. Luque, Asymptotic convergence analysis of the proximal point algorithm,, SIAM Journal on Control and Optimization, 22 (1984), 277.  doi: 10.1137/0322019.  Google Scholar [27] B. Martinet, Perturbation des méthodes d'opimisation,, RAIRO Anal. Numér., 12 (1978), 153.   Google Scholar [28] R. Mifflin, Semismooth and semiconvex functions in constrained optimization,, SIAM Journal on Control and Optimization, 15 (1997), 957.   Google Scholar [29] J.-S. Pang, A posteriori error bounds for the linearly-constrained variational inequality problem,, Mathematics of Operations Research, 12 (1987), 474.  doi: 10.1287/moor.12.3.474.  Google Scholar [30] J.-S. Pang, Complementarity problems,, in, (1994), 271.   Google Scholar [31] J.-S. Pang and L. Qi, Nonsmooth equations: Motivation and algorithms,, SIAM Journal on Optimization, 3 (1993), 443.  doi: 10.1137/0803021.  Google Scholar [32] L. Qi, A convergence analysis of some algorithms for solving nonsmooth equations,, Mathematics of Operations Research, 18 (1993), 227.  doi: 10.1287/moor.18.1.227.  Google Scholar [33] L. Qi and J. Sun, A nonsmooth version of Newton's method,, Mathematical Programming, 58 (1993), 353.  doi: 10.1007/BF01581275.  Google Scholar [34] S. M. Robinson, Strongly regular generalized equations,, Mathematics of Operations Research, 5 (1980), 43.  doi: 10.1287/moor.5.1.43.  Google Scholar [35] R. T. Rockafellar, Monotone operators and the proximal point algorithm,, SIAM Journal on Control and Optimization, 14 (1976), 877.  doi: 10.1137/0314056.  Google Scholar [36] R. T. Rockafellar and R. J-B. Wets, "Variational Analysis,", Springer-Verlag Berlin Heidelberg, (1998).  doi: 10.1007/978-3-642-02431-3.  Google Scholar [37] D. Sun and L. Qi, On NCP-functions,, Computational Optimization and Applications, 13 (1999), 201.  doi: 10.1023/A:1008669226453.  Google Scholar [38] D. Sun and J. Sun, Strong semismoothness of the Fischer-Burmeister SDC and SOC complementarity functions,, Mathematical Programming, 103 (2005), 575.  doi: 10.1007/s10107-005-0577-4.  Google Scholar [39] J. Wu and J.-S. Chen, A proximal point algorithm for the monotone second-order cone complementarity problem,, Computational Optimization and Applications, 51 (2012), 1037.   Google Scholar [40] N. Yamashita and M. Fukushima, On stationary points of the implicitm Lagrangian for nonlinear complementarity problems,, Journal of Optimization Theory and Applications, 84 (1995), 653.  doi: 10.1007/BF02191990.  Google Scholar [41] N. Yamashita and M. Fukushima, Modified Newton methods for solving a semismooth reformulation of monotone complementarity problems,, Mathematical Programming, 76 (1997), 469.   Google Scholar [42] N. Yamashita and M. Fukushima, The proximal point algorithm with genuine superlinear convergence for the monotone complementarity problem,, SIAM Journal on Optimization, 11 (2000), 364.  doi: 10.1137/S105262349935949X.  Google Scholar [43] N. Yamashita, J. Imai and M. Fukushima, The proximal point algorithm for the $P_0$ complementarity problem,, in, (2001), 361.   Google Scholar
 [1] Sandrine Anthoine, Jean-François Aujol, Yannick Boursier, Clothilde Mélot. Some proximal methods for Poisson intensity CBCT and PET. Inverse Problems & Imaging, 2012, 6 (4) : 565-598. doi: 10.3934/ipi.2012.6.565 [2] J. Frédéric Bonnans, Justina Gianatti, Francisco J. Silva. On the convergence of the Sakawa-Shindo algorithm in stochastic control. Mathematical Control & Related Fields, 2016, 6 (3) : 391-406. doi: 10.3934/mcrf.2016008 [3] Vakhtang Putkaradze, Stuart Rogers. Numerical simulations of a rolling ball robot actuated by internal point masses. Numerical Algebra, Control & Optimization, 2021, 11 (2) : 143-207. doi: 10.3934/naco.2020021 [4] Demetres D. Kouvatsos, Jumma S. Alanazi, Kevin Smith. A unified ME algorithm for arbitrary open QNMs with mixed blocking mechanisms. Numerical Algebra, Control & Optimization, 2011, 1 (4) : 781-816. doi: 10.3934/naco.2011.1.781 [5] Zhihua Zhang, Naoki Saito. PHLST with adaptive tiling and its application to antarctic remote sensing image approximation. Inverse Problems & Imaging, 2014, 8 (1) : 321-337. doi: 10.3934/ipi.2014.8.321 [6] Luke Finlay, Vladimir Gaitsgory, Ivan Lebedev. Linear programming solutions of periodic optimization problems: approximation of the optimal control. Journal of Industrial & Management Optimization, 2007, 3 (2) : 399-413. doi: 10.3934/jimo.2007.3.399 [7] Xianming Liu, Guangyue Han. A Wong-Zakai approximation of stochastic differential equations driven by a general semimartingale. Discrete & Continuous Dynamical Systems - B, 2021, 26 (5) : 2499-2508. doi: 10.3934/dcdsb.2020192 [8] Enkhbat Rentsen, Battur Gompil. Generalized Nash equilibrium problem based on malfatti's problem. Numerical Algebra, Control & Optimization, 2021, 11 (2) : 209-220. doi: 10.3934/naco.2020022 [9] Alexandr Mikhaylov, Victor Mikhaylov. Dynamic inverse problem for Jacobi matrices. Inverse Problems & Imaging, 2019, 13 (3) : 431-447. doi: 10.3934/ipi.2019021 [10] Armin Lechleiter, Tobias Rienmüller. Factorization method for the inverse Stokes problem. Inverse Problems & Imaging, 2013, 7 (4) : 1271-1293. doi: 10.3934/ipi.2013.7.1271 [11] Hildeberto E. Cabral, Zhihong Xia. Subharmonic solutions in the restricted three-body problem. Discrete & Continuous Dynamical Systems - A, 1995, 1 (4) : 463-474. doi: 10.3934/dcds.1995.1.463 [12] Michel Chipot, Mingmin Zhang. On some model problem for the propagation of interacting species in a special environment. Discrete & Continuous Dynamical Systems - A, 2020  doi: 10.3934/dcds.2020401 [13] Fritz Gesztesy, Helge Holden, Johanna Michor, Gerald Teschl. The algebro-geometric initial value problem for the Ablowitz-Ladik hierarchy. Discrete & Continuous Dynamical Systems - A, 2010, 26 (1) : 151-196. doi: 10.3934/dcds.2010.26.151 [14] Gloria Paoli, Gianpaolo Piscitelli, Rossanno Sannipoli. A stability result for the Steklov Laplacian Eigenvalue Problem with a spherical obstacle. Communications on Pure & Applied Analysis, 2021, 20 (1) : 145-158. doi: 10.3934/cpaa.2020261 [15] Hailing Xuan, Xiaoliang Cheng. Numerical analysis and simulation of an adhesive contact problem with damage and long memory. Discrete & Continuous Dynamical Systems - B, 2021, 26 (5) : 2781-2804. doi: 10.3934/dcdsb.2020205 [16] Marco Ghimenti, Anna Maria Micheletti. Compactness results for linearly perturbed Yamabe problem on manifolds with boundary. Discrete & Continuous Dynamical Systems - S, 2021, 14 (5) : 1757-1778. doi: 10.3934/dcdss.2020453 [17] Hailing Xuan, Xiaoliang Cheng. Numerical analysis of a thermal frictional contact problem with long memory. Communications on Pure & Applied Analysis, , () : -. doi: 10.3934/cpaa.2021031 [18] Rongchang Liu, Jiangyuan Li, Duokui Yan. New periodic orbits in the planar equal-mass three-body problem. Discrete & Continuous Dynamical Systems - A, 2018, 38 (4) : 2187-2206. doi: 10.3934/dcds.2018090 [19] Marion Darbas, Jérémy Heleine, Stephanie Lohrengel. Numerical resolution by the quasi-reversibility method of a data completion problem for Maxwell's equations. Inverse Problems & Imaging, 2020, 14 (6) : 1107-1133. doi: 10.3934/ipi.2020056 [20] Namsu Ahn, Soochan Kim. Optimal and heuristic algorithms for the multi-objective vehicle routing problem with drones for military surveillance operations. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021037

2019 Impact Factor: 1.366