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  • Articles  (4)
  • Other Sources
  • Global optimization
  • 2000-2004
  • 1985-1989  (4)
  • 1988  (4)
  • Mathematics  (4)
Collection
  • Articles  (4)
  • Other Sources
Source
Keywords
Publisher
Years
  • 2000-2004
  • 1985-1989  (4)
Year
Topic
  • 1
    Electronic Resource
    Electronic Resource
    Quadratic problems defined on a convex hull of points (1988)
    Springer
    BIT 28 (1988), S. 323-328 
    Details
    ISSN: 1572-9125
    Keywords: 90C30 ; 65K05 ; Global optimization ; Quadratic programming ; Convex hull
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract In this paper we consider an algorithm for a class of quadratic problems defined on a polytope which is described as the convex hull of a set of points. The algorithm is based on simplex partitions using convex underestimating functions.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01934095
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    Paper (German National Licenses)
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  • 2
    Electronic Resource
    Electronic Resource
    Convergence and restart in branch-and-bound algorithms for global optimization. Application to concave minimization and D.C. Optimization problems (1988)
    Springer
    Mathematical programming 41 (1988), S. 161-183 
    Details
    ISSN: 1436-4646
    Keywords: Global optimization ; nonconvex programming ; branch-and-bound ; restart procedure ; decomposition ; outer approximation ; concave minimization ; d.c. optimization
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract A general branch-and-bound conceptual scheme for global optimization is presented that includes along with previous branch-and-bound approaches also grid-search techniques. The corresponding convergence theory, as well as the question of restart capability for branch-and-bound algorithms used in decomposition or outer approximation schemes are discussed. As an illustration of this conceptual scheme, a finite branch-and-bound algorithm for concave minimization is described and a convergent branch-and-bound algorithm, based on the previous one, is developed for the minimization of a difference of two convex functions.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01580762
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  • 3
    Electronic Resource
    Electronic Resource
    Deterministic global optimization with partition sets whose feasibility is not known: Application to concave minimization, reverse convex constraints, DC-programming, and Lipschitzian optimization (1988)
    Springer
    Journal of optimization theory and applications 58 (1988), S. 11-37 
    Details
    ISSN: 1573-2878
    Keywords: Global optimization ; nonconvex programming ; mathematical programming ; concave minimization ; DC-programming ; Lipschitzian optimization ; branch-and-bound methods
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract A crucial problem for many global optimization methods is how to handle partition sets whose feasibility is not known. This problem is solved for broad classes of feasible sets including convex sets, sets defined by finitely many convex and reverse convex constraints, and sets defined by Lipschitzian inequalities. Moreover, a fairly general theory of bounding is presented and applied to concave objective functions, to functions representable as differences of two convex functions, and to Lipschitzian functions. The resulting algorithms allow one to solve any global optimization problem whose objective function is of one of these forms and whose feasible set belongs to one of the above classes. In this way, several new fields of optimization are opened to the application of global methods.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00939768
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  • 4
    Electronic Resource
    Electronic Resource
    An algorithm for global optimization of Lipschitz continuous functions (1988)
    Springer
    Journal of optimization theory and applications 57 (1988), S. 307-322 
    Details
    ISSN: 1573-2878
    Keywords: Global optimization ; nondifferentiable optimization ; Lipschitz continuous functions
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract An algorithm is presented which locates the global minimum or maximum of a function satisfying a Lipschitz condition. The algorithm uses lower bound functions defined on a partitioned domain to generate a sequence of lower bounds for the global minimum. Convergence is proved, and some numerical results are presented.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00938542
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