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  • Articles: DFG German National Licenses  (5)
  • global convergence  (3)
  • Linear program  (2)
  • 1
    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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  • 2
    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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  • 3
    Electronic Resource
    Electronic Resource
    Springer
    Annals of operations research 62 (1996), S. 1-28 
    ISSN: 1572-9338
    Keywords: Linear program ; interior point method ; initial point ; step length ; complementarity problem ; polynomial-time complexity
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Notes: Abstract The primal-dual infeasible-interior-point algorithm is known as one of the most efficient computational methods for linear programs. Recently, a polynomial-time computational complexity bound was established for special variants of the algorithm. However, they impose severe restrictions on initial points and require a common step length in the primal and dual spaces. This paper presents some basic lemmas that bring great flexibility and improvement into such restrictions on initial points and step lengths, and discusses their extensions to linear and nonlinear monotone complementarity problems.
    Type of Medium: Electronic Resource
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  • 4
    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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  • 5
    Electronic Resource
    Electronic Resource
    Springer
    Algorithmica 1 (1986), S. 499-515 
    ISSN: 1432-0541
    Keywords: Linear program ; Karmarkar's algorithm ; Optimal basis
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract This paper establishes a sufficient condition for a variable of a linear program to be positive at all optimal solutions. A numerical test using the condition is incorporated into Karmarkar's new LP algorithm to determine columns of optimal basis. Experimental results on the test are also reported.
    Type of Medium: Electronic Resource
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