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  • 11
    Electronic Resource
    Electronic Resource
    Springer
    Journal of global optimization 10 (1997), S. 367-380 
    ISSN: 1573-2916
    Keywords: Semidefinite program ; relaxation method ; interior-point method ; nonconvex quadratic program ; linear matrix inequality
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract This paper applies the SDP (semidefinite programming)relaxation originally developed for a 0-1 integer program to ageneral nonconvex QP (quadratic program) having a linear objective functionand quadratic inequality constraints, and presents some fundamental characterizations of the SDP relaxation including its equivalence to arelaxation using convex-quadratic valid inequalities for the feasible regionof the QP.
    Type of Medium: Electronic Resource
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  • 12
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 16 (1979), S. 37-62 
    ISSN: 1436-4646
    Keywords: Roots of Polynomials ; Fixed Point Computing Methods ; Complementary Pivoting Methods ; Piecewise Linear Homotopy
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract This paper presents a constructive method which gives, for any polynomialF(Z) of the degreen, approximate values of all the roots ofF(Z).. The point of the method is on the use of a piecewise linear function $$\bar H$$ (Z, t) which approximates a homotopyH(Z, t) betweenF(Z) and a polynomialG(Z) of the degreen withn known simple roots. It is shown that the set of solutions to $$\bar H$$ (Z, t) = 0 includesn distinct paths,m of which converges to a root ofF(Z) if and only if the root has the multiplicitym. Starting from givenn roots ofG(Z), a complementary pivot algorithm generates thosen paths.
    Type of Medium: Electronic Resource
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  • 13
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 15 (1978), S. 223-227 
    ISSN: 1436-4646
    Keywords: Triangulations ; Fixed Point Computing Methods ; Complementary Pivoting Methods ; Piecewise Linear Homotopy
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract When we apply the fixed point computing method to mappings which are affine in some variables, we show that, to generate a sequence which converges to a fixed point, the mesh size need not be decreased in these coordinates. This paper modifies the triangulationJ 3 with continuous refinement of mesh size to a triangulation $$\bar J_3$$ such that the mesh size of $$\bar J_3$$ in some given coordinates is constant and the mesh size in the other coordinates shrinks to zero.
    Type of Medium: Electronic Resource
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  • 14
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 48 (1990), S. 415-435 
    ISSN: 1436-4646
    Keywords: Linear complementarity problem ; ellipsoid ; interior point algorithm ; path following algorithm
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract This paper deals with the LCP (linear complementarity problem) with a positive semi-definite matrix. Assuming that a strictly positive feasible solution of the LCP is available, we propose ellipsoids each of which contains all the solutions of the LCP. We use such an ellipsoid for computing a lower bound and an upper bound for each coordinate of the solutions of the LCP. We can apply the lower bound to test whether a given variable is positive over the solution set of the LCP. That is, if the lower bound is positive, we know that the variable is positive over the solution set of the LCP; hence, by the complementarity condition, its complement is zero. In this case we can eliminate the variable and its complement from the LCP. We also show how we efficiently combine the ellipsoid method for computing bounds for the solution set with the path-following algorithm proposed by the authors for the LCP. If the LCP has a unique non-degenerate solution, the lower bound and the upper bound for the solution, computed at each iteration of the path-following algorithm, both converge to the solution of the LCP.
    Type of Medium: Electronic Resource
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  • 15
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 24 (1982), S. 177-215 
    ISSN: 1436-4646
    Keywords: Variable Dimension Algorithm ; Fixed Point ; Subdivided Manifold ; Nonlinear Equations
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract In this paper we establish a basic theory for variable dimension algorithms which were originally developed for computing fixed points by Van der Laan and Talman. We introduce a new concept ‘primal—dual pair of subdivided manifolds’ and by utilizing it we propose a basic model which will serve as a foundation for constructing a wide class of variable dimension algorithms. Our basic model furnishes interpretations to several existing methods: Lemke's algorithm for the linear complementarity problem, its extension to the nonlinear complementarity problem, a variable dimension algorithm on conical subdivisions and Merrill's algorithm. We shall present a method for solving systems of equations as an application of the second method and an efficient implementation of the fourth method to which our interpretation leads us. A method for constructing triangulations with an arbitrary refinement factor of mesh size is also proposed.
    Type of Medium: Electronic Resource
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  • 16
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 50 (1991), S. 331-342 
    ISSN: 1436-4646
    Keywords: Potential reduction algorithm ; linear complementarity problem ; interior point algorithm ; Karmarkar's algorithm ; path of centers ; central trajectory
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract This paper proposes an interior point algorithm for a positive semi-definite linear complementarity problem: find an (x, y)∈ℝ 2n such thaty=Mx+q, (x,y)⩾0 andx T y=0. The algorithm reduces the potential function $$f(x,y) = (n + \sqrt n )\log x^T y - \sum\limits_{i = 1}^n {\log x_i y_i } $$ by at least 0.2 in each iteration requiring O(n 3) arithmetic operations. If it starts from an interior feasible solution with the potential function value bounded by $$O(\sqrt n L)$$ , it generates, in at most $$O(\sqrt n L)$$ iterations, an approximate solution with the potential function value $$ - O(\sqrt n L)$$ , from which we can compute an exact solution in O(n 3) arithmetic operations. The algorithm is closely related with the central path following algorithm recently given by the authors. We also suggest a unified model for both potential reduction and path following algorithms for positive semi-definite linear complementarity problems.
    Type of Medium: Electronic Resource
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  • 17
    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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  • 18
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 62 (1993), S. 85-93 
    ISSN: 1436-4646
    Keywords: Bigℳ ; affine scaling algorithm ; linear program ; interior point algorithm ; infeasibility ; global convergence
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract When we apply the affine scaling algorithm to a linear program, we usually construct an artificial linear program having an interior feasible solution from which the algorithm starts. The artificial linear program involves a positive number called the bigℳ. Theoretically, there exists anℳ * such that the original problem to be solved is equivalent to the artificial linear program ifℳ 〉ℳ *. Practically, however, such anℳ * is unknown and a safe estimate ofℳ is often too large. This paper proposes a method of updatingℳ to a suitable value during the iteration of the affine scaling algorithm. Asℳ becomes large, the method gives information on infeasibility of the original problem or its dual.
    Type of Medium: Electronic Resource
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  • 19
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 9 (1975), S. 257-277 
    ISSN: 1436-4646
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract The nonlinear complementarity problem is the problem of finding a point x in the n-dimensional Euclidean space,R n , such that x ⩾ 0, f(x) ⩾ 0 and 〈x,f(x)∼ = 0, where f is a nonlinear continuous function fromR n into itself. Many existence theorems for the problem have been established in various ways. The aim of the present paper is to treat them in a unified manner. Eaves's basic theorem of complementarity is generalized, and the generalized theorem is used as a unified framework for several typical existence theorems.
    Type of Medium: Electronic Resource
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  • 20
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 65 (1994), S. 43-72 
    ISSN: 1436-4646
    Keywords: Monotone complementarity problem ; Interior-point algorithm ; Potential reduction algorithm ; Infeasibility ; Global convergence
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract This paper presents a wide class of globally convergent interior-point algorithms for the nonlinear complementarity problem with a continuously differentiable monotone mapping in terms of a unified global convergence theory given by Polak in 1971 for general nonlinear programs. The class of algorithms is characterized as: Move in a Newton direction for approximating a point on the path of centers of the complementarity problem at each iteration. Starting from a strictly positive but infeasible initial point, each algorithm in the class either generates an approximate solution with a given accuracy or provides us with information that the complementarity problem has no solution in a given bounded set. We present three typical examples of our interior-point algorithms, a horn neighborhood model, a constrained potential reduction model with the use of the standard potential function, and a pure potential reduction model with the use of a new potential function.
    Type of Medium: Electronic Resource
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