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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 82 (1998), S. 339-355 
    ISSN: 1436-4646
    Keywords: Linear programming ; Layered-step interior-point method ; Path of centers ; Crossover events
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract The layered-step interior-point algorithm was introduced by Vavasis and Ye. The algorithm accelerates the path following interior-point algorithm and its arithmetic complexity depends only on the coefficient matrixA. The main drawback of the algorithm is the use of an unknown big constant $$\bar \chi _A $$ in computing the search direction and to initiate the algorithm. We propose a modified layered-step interior-point algorithm which does not use the big constant in computing the search direction. The constant is required only for initialization when a well-centered feasible solution is not available, and it is not required if an upper bound on the norm of a primal—dual optimal solution is known in advance. The complexity of the simplified algorithm is the same as that of Vavasis and Ye. © 1998 The Mathematical Programming Society, Inc. Published by Elsevier Science B.V.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 44 (1989), S. 1-26 
    ISSN: 1436-4646
    Keywords: Linear complementarity problem ; polynomial-time algorithm ; path of centers ; Karmarkar's algorithm
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract Given ann × n matrixM and ann-dimensional vectorq, the problem of findingn-dimensional vectorsx andy satisfyingy = Mx + q, x ≥ 0,y ≥ 0,x i y i = 0 (i = 1, 2,⋯,n) is known as a linear complementarity problem. Under the assumption thatM is positive semidefinite, this paper presents an algorithm that solves the problem in O(n 3 L) arithmetic operations by tracing the path of centers,{(x, y) ∈ S: x i y i =μ (i = 1, 2,⋯,n) for some μ 〉 0} of the feasible regionS = {(x, y) ≥ 0:y = Mx + q}, whereL denotes the size of the input data of the problem.
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 67 (1994), S. 109-119 
    ISSN: 1436-4646
    Keywords: Polynomial-time ; Linear programming ; Primal-dual ; Interior-point algorithm
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract Kojima, Megiddo, and Mizuno investigate an infeasible-interior-point algorithm for solving a primal—dual pair of linear programming problems and they demonstrate its global convergence. Their algorithm finds approximate optimal solutions of the pair if both problems have interior points, and they detect infeasibility when the sequence of iterates diverges. Zhang proves polynomial-time convergence of an infeasible-interior-point algorithm under the assumption that both primal and dual problems have feasible points. In this paper, we show that a modification of the Kojima—Megiddo—Mizuno algorithm “solves” the pair of problems in polynomial time without assuming the existence of the LP solution. Furthermore, we develop anO(nL)-iteration complexity result for a variant of the algorithm.
    Type of Medium: Electronic Resource
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  • 4
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 56 (1992), S. 31-43 
    ISSN: 1436-4646
    Keywords: Linear complementarity problem ; polynomial time method ; path following method ; potential reduction method
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: 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).
    Type of Medium: Electronic Resource
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  • 5
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 84 (1999), S. 105-122 
    ISSN: 1436-4646
    Keywords: Key words: linear programming problem – interior-point method – primal-dual – convergence – inexact computation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Type of Medium: Electronic Resource
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  • 6
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 43 (1989), S. 107-113 
    ISSN: 1436-4646
    Keywords: Complementarity problem ; continuation method ; P-function ; homeomorphism
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract The complementarity problem with a nonlinear continuous mappingf from the nonnegative orthantR + n ofR n intoR n can be written as the system of equationsF(x, y) = 0 and(x, y) ∈ R + 2n , whereF denotes the mapping from the nonnegative orthantR + 2n ofR 2n intoR + n × Rn defined byF(x, y) = (x 1y1,⋯,xnyn, f1(x) − y1,⋯, fn(x) − yn) for every(x, y) ∈ R + 2n . Under the assumption thatf is a uniformP-function, this paper establishes that the mappingF is a homeomorphism ofR + 2n ontoR + n × Rn. This result provides a theoretical basis for a new continuation method of tracing the solution curve of the one parameter family of systems of equationsF(x, y) = tF(x 0, y0) and(x, y) ∈ R + 2n from an arbitrary initial point(x 0, y0) ∈ R + 2n witht = 1 until the parametert attains 0. This approach is an extension of the one used in the polynomially bounded algorithm recently given by Kojima, Mizuno and Yoshise for solving linear complementarity problems with positive semi-definite matrices.
    Type of Medium: Electronic Resource
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  • 7
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 59 (1993), S. 361-375 
    ISSN: 1436-4646
    Keywords: Interior point algorithm ; big ℳ ; linear program ; convex program ; complementarity problem ; potential reduction algorithm ; self-dual linear program
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract When we apply interior point algorithms to various problems including linear programs, convex quadratic programs, convex programs and complementarity problems, we often embed an original problem to be solved in an artificial problem having a known interior feasible solution from which we start the algorithm. The artificial problem involves a constantℳ (or constants) which we need to choose large enough to ensure the equivalence between the artificial problem and the original problem. Theoretically, we can always assign a positive number of the order O(2 L ) toℳ in linear cases, whereL denotes the input size of the problem. Practically, however, such a large number is impossible to implement on computers. If we choose too largeℳ, we may have numerical instability and/or computational inefficiency, while the artificial problem withℳ not large enough will never lead to any solution of the original problem. To solve this difficulty, this paper presents “a little theorem of the bigℳ”, which will enable us to find whetherℳ is not large enough, and to updateℳ during the iterations of the algorithm even if we start with a smallerℳ. Applications of the theorem are given to a polynomial-time potential reduction algorithm for positive semi-definite linear complementarity problems, and to an artificial self-dual linear program which has a close relation with the primal—dual interior point algorithm using Lustig's limiting feasible direction vector.
    Type of Medium: Electronic Resource
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  • 8
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 61 (1993), S. 263-280 
    ISSN: 1436-4646
    Keywords: Infeasible-interior-point algorithm ; interior-point algorithm ; primal—dual algorithm ; linear program ; large step ; global convergence
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract As in many primal—dual interior-point algorithms, a primal—dual infeasible-interior-point algorithm chooses a new point along the Newton direction towards a point on the central trajectory, but it does not confine the iterates within the feasible region. This paper proposes a step length rule with which the algorithm takes large distinct step lengths in the primal and dual spaces and enjoys the global convergence.
    Type of Medium: Electronic Resource
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  • 9
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 59 (1993), S. 1-21 
    ISSN: 1436-4646
    Keywords: Primal—dual interior point algorithm ; linear program ; large step ; global convergence ; polynomial-time convergence
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract This paper proposes two sets of rules, Rule G and Rule P, for controlling step lengths in a generic primal—dual interior point method for solving the linear programming problem in standard form and its dual. Theoretically, Rule G ensures the global convergence, while Rule P, which is a special case of Rule G, ensures the O(nL) iteration polynomial-time computational complexity. Both rules depend only on the lengths of the steps from the current iterates in the primal and dual spaces to the respective boundaries of the primal and dual feasible regions. They rely neither on neighborhoods of the central trajectory nor on potential function. These rules allow large steps without performing any line search. Rule G is especially flexible enough for implementation in practically efficient primal—dual interior point algorithms.
    Type of Medium: Electronic Resource
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  • 10
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 59 (1993), S. 23-31 
    ISSN: 1436-4646
    Keywords: Linear programming ; duality theorem ; unimodular ; totally unimodular ; interior point methods
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract In this paper we consider a linear programming problem with the underlying matrix unimodular, and the other data integer. Given arbitrary near optimum feasible solutions to the primal and the dual problems, we obtain conditions under which statements can be made about the value of certain variables in optimal vertices. Such results have applications to the problem of determining the stopping criterion in interior point methods like the primal—dual affine scaling method and the path following methods for linear programming.
    Type of Medium: Electronic Resource
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