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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Journal of global optimization 2 (1992), S. 201-208 
    ISSN: 1573-2916
    Keywords: Global optimization ; quadratic program ; lower bound ; branch and bound
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract In this paper we prove a sufficient condition that a strong local minimizer of a bounded quadratic program is the unique global minimizer. This sufficient condition can be verified computationally by solving a linear and a convex quadratic program and can be used as a quality test for local minimizers found by standard indefinite quadratic programming routines.
    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 global optimization 9 (1996), S. 141-151 
    ISSN: 1573-2916
    Keywords: Global optimization ; optimality condition ; second-order sufficient condition ; verification of convexity ; interval analysis ; primary 90C30 ; secondary 65G10
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract This paper presents a new approach to the sufficient conditions of nonlinear programming. Main result is a sufficient condition for the global optimality of a Kuhn-Tucker point. This condition can be verified constructively, using a novel convexity test based on interval analysis, and is guaranteed to prove global optimality of strong local minimizers for sufficiently narrow bounds. Hence it is expected to be a useful tool within branch and bound algorithms for global optimization.
    Type of Medium: Electronic Resource
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    Electronic Resource
    Electronic Resource
    Springer
    Journal of global optimization 14 (1999), S. 331-355 
    ISSN: 1573-2916
    Keywords: Global optimization ; Bound constraints ; Local optimization ; Coordinate search
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract Inspired by a method by Jones et al. (1993), we present a global optimization algorithm based on multilevel coordinate search. It is guaranteed to converge if the function is continuous in the neighborhood of a global minimizer. By starting a local search from certain good points, an improved convergence result is obtained. We discuss implementation details and give some numerical results.
    Type of Medium: Electronic Resource
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