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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Annals of operations research 46-47 (1993), S. 107-138 
    ISSN: 1572-9338
    Keywords: Linear programming ; interior point methods ; degeneracy ; polynomial algorithms ; global and local convergence ; basis recovery ; numerical performance ; sensitivity analysis
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Notes: Abstract The publication of Karmarkar's paper has resulted in intense research activity into Interior Point Methods (IPMs) for linear programming. Degeneracy is present in most real-life problems and has always been an important issue in linear programming, especially in the Simplex method. Degeneracy is also an important issue in IPMs. However, the difficulties are different in the two methods. In this paper, we survey the various theoretical and practical issues related to degeneracy in IPMs for linear programming. We survey results, which, for the most part, have already appeared in the literature. Roughly speaking, we shall deal with the effect of degeneracy on the following: the convergence of IPMs, the trajectories followed by the algorithms, numerical performance, and finding basic solutions.
    Type of Medium: Electronic Resource
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Journal of optimization theory and applications 87 (1995), S. 703-726 
    ISSN: 1573-2878
    Keywords: Linear programming ; interior-point methods ; Iri-Imai algorithm ; local analysis ; degenerate problems
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract A local analysis of the Iri-Imai algorithm for linear programming is given to demonstrate quadratic convergence under degeneracy. Specifically, we show that the algorithm with an exact line search either terminates after a finite number of iterations yielding a point on the set of optimal solutions or converges quadratically to one of the relative analytic centers of the faces of the set of optimal solutions including vertices. Mostly, the sequence generated falls into one of the optimal vertices, and it is rare that the sequence converges to the relative analytic center of a face whose dimension is greater than or equal to one.
    Type of Medium: Electronic Resource
    Library Location Call Number Volume/Issue/Year Availability
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