Abstract
The purpose of this paper is to present a new polynomial time method for a linear complementarity problem with a positive semi-definite matrix. The method follows a sequence of points. If we generate the sequence on a path, we can construct a path following method, and if we generate the sequence based on a potential function, we can construct a potential reduction method. The method has the advantage that it requires at most\(O(\sqrt n L)\) iterations for any initial feasible point whose components lie between 2−O(L) and 2O(L).
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References
R.W. Cottle and G.B. Dantzig, “Complementary pivot theory of mathematical programming,”Linear Algebra and its Applications 1 (1968) 103–125.
R.M. Freund, “Polynomial-time algorithms for linear programming based only on primal scaling and projected gradients of a potential function,”Mathematical Programming 51 (1991) 203–222.
C.C. Gonzaga, “An algorithm for solving linear programming programs in O(n 3 L) operations,” in: N. Megiddo, ed.,Progress in Mathematical Programming, Interior Point and Related Methods (Springer, New York, 1988) pp. 1–28.
N. Karmarkar, “A new polynomial-time algorithm for linear programming,”Combinatorica 4 (1984) 373–395.
M. Kojima, N. Megiddo and Y. Ye, “An interior point potential reduction algorithm for the linear complementarity problem,”Mathematical Programming 54 (1992) 267–279.
M. Kojima, S. Mizuno and A. Yoshise, “A polynomial-time algorithm for a class of linear complementarity problems,”Mathematical Programming 44 (1989) 1–26.
M. Kojima, S. Mizuno and A. Yoshise, “An\(O(\sqrt n L)\) iteration potential reduction algorithm for linear complementarity problems,”Mathematical Programming 50 (1991) 331–342.
M. Kojima, S. Mizuno and A. Yoshise, “A primal—dual interior point algorithm for linear programming,” in: N. Megiddo, ed.,Progress in Mathematical Programming, Interior Point and Related Methods (Springer, New York, 1988) pp. 29–47.
C.E. Lemke, “Bimatrix equilibrium points and mathematical programming,”Management Science 11 (1965) 681–689.
N. Megiddo, “Pathways to the optimal set in linear programming,” in: N. Megiddo, ed.,Progress in Mathematical Programming, Interior Point and Related Methods (Springer, New York, 1988) pp. 131–158.
S. Mizuno, A. Yoshise and T. Kikuchi, “Practical polynomial time algorithms for linear complementarity problems,”Journal of the Operations Research Society of Japan 32 (1989) 75–92.
R.C. Monteiro and I. Adler, “Interior point path following primal-dual algorithms. Part I: Linear programming,”Mathematical Programming 44 (1989) 27–42.
J. Renegar, “A polynomial-time algorithm based on Newton's method for linear programming,”Mathematical Programming 40 (1988) 59–94.
M.J. Todd, “Recent developments and new directions in linear programming,” in: M. Iri and K. Tanabe, eds.,Mathematical Programming (Kluwer Academic Publishers, 1989) pp. 109–157.
M.J. Todd and Y. Ye, “A centered projective algorithm for linear programming,”Mathematics of Operations Research 15 (1990) 508–529.
Y. Ye, “An O(n 3 L) potential reduction algorithm for linear programming,”Mathematical Programming 50 (1991) 239–258.
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Research was supported in part by Grant-in-Aids for Encouragement of Young Scientists (63730014) and for General Scientific Research (63490010) of The Ministry of Education, Science and Culture.
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Mizuno, S. A new polynomial time method for a linear complementarity problem. Mathematical Programming 56, 31–43 (1992). https://doi.org/10.1007/BF01580891
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DOI: https://doi.org/10.1007/BF01580891