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  • 1
    Electronic Resource
    Electronic Resource
    Oxford, UK : Blackwell Publishing Ltd
    Journal of regional science 32 (1992), S. 0 
    ISSN: 1467-9787
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Geography , Economics
    Notes: . Weber's problem consists of locating a facility in the plane in such a way that the weighted sum of Euclidean distances to n given points be minimum. The case where some weights are positive and some are negative is shown to be a d.-c. program (i.e., a global optimization problem with both the objective function and constraint functions written as differences of convex functions), reducible to a problem of concave minimization over a convex set. The reduced problem is then solved by outer-approximation and vertex enumeration. Moreover, locational constraints can be taken into account by combining the previous algorithm with an enumerative procedure on the set of feasible regions. Finally, the algorithm is extended to solve the case where obnoxiousness of the facility is assumed to have exponential decay. Computational experience with n up to 1000 is described.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 16 (1979), S. 210-227 
    ISSN: 1436-4646
    Keywords: Pivotal Algorithms ; Equilibrium Point ; Primitive Sets ; Restart Method
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract On the basis of a unified approach to pivotal algorithms and a generalization of the concept of primitive sets by Scarf we show that Scarf's algorithm for finding fixed points can be embedded into a class of more flexible and more efficient algorithms, allowing restarts. An example of this new restart method is described. Also the class of equilibrium problems solvable by this method is discussed.
    Type of Medium: Electronic Resource
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  • 3
    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
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  • 4
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 51 (1991), S. 229-245 
    ISSN: 1436-4646
    Keywords: Concave minimization ; conical algorithm ; convergence condition ; bisection ; normal subdivision process
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract A new conical algorithm is developed for finding the global minimum of a concave function over a polytope. To ensure faster convergence and overcome some major drawbacks of previous conical algorithms, a normal (rather than exhaustive) subdivision process is used.
    Type of Medium: Electronic Resource
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  • 5
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 85 (1999), S. 157-179 
    ISSN: 1436-4646
    Keywords: Key words: transportation – d.c. functions – decomposition methods – branch-and-bound ; Mathematics Subject Classification (1991): 90C26, 90B06
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Well known extensions of the classical transportation problem are obtained by including fixed costs for the production of goods at the supply points (facility location) and/or by introducing stochastic demand, modeled by convex nonlinear costs, at the demand points (the stochastic transportation problem, [STP]). However, the simultaneous use of concave and convex costs is not very well treated in the literature. Economies of scale often yield concave cost functions other than fixed charges, so in this paper we consider a problem with general concave costs at the supply points, as well as convex costs at the demand points. The objective function can then be represented as the difference of two convex functions, and is therefore called a d.c. function. We propose a solution method which reduces the problem to a d.c. optimization problem in a much smaller space, then solves the latter by a branch and bound procedure in which bounding is based on solving subproblems of the form of [STP]. We prove convergence of the method and report computational tests that indicate that quite large problems can be solved efficiently. Problems up to the size of 100 supply points and 500 demand points are solved.
    Type of Medium: Electronic Resource
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  • 6
    Electronic Resource
    Electronic Resource
    Springer
    Applied mathematics & optimization 18 (1988), S. 119-142 
    ISSN: 1432-0606
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract The problem of globally minimizing a convex function subject to general continuous inequality constraints is investigated. A convergent outer approximation method is proposed which systematically exploits the convexity of the objective function in order to transcend local optimality. Also the question of finding a good starting point by using a local approach is discussed.
    Type of Medium: Electronic Resource
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  • 7
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical notes 9 (1971), S. 250-253 
    ISSN: 1573-8876
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract The class of almost affine functions is investigated. A function is called almost-affine if, on any segment contained in its domain of definition (supposed convex), it is either constant or monotonic.
    Type of Medium: Electronic Resource
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  • 8
    Electronic Resource
    Electronic Resource
    Springer
    Journal of global optimization 4 (1994), S. 243-263 
    ISSN: 1573-2916
    Keywords: Linear two-level program ; global optimization ; Stackelberg game ; quasiconcave minimization ; branch and bound ; outer approximation ; subdivision procedure
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract In this paper the linear two-level problem is considered. The problem is reformulated to an equivalent quasiconcave minimization problem, via a reverse convex transformation. A branch and bound algorithm is developed which takes the specific structure into account and combines an outer approximation technique with a subdivision procedure.
    Type of Medium: Electronic Resource
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  • 9
    Electronic Resource
    Electronic Resource
    Springer
    Journal of global optimization 7 (1995), S. 209-227 
    ISSN: 1573-2916
    Keywords: Facility location ; d.c optimization ; global optimization ; nondifferentiable optimization
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract The single facility location problem with general attraction and repulsion functions is considered. An algorithm based on a representation of the objective function as the difference of two convex (d.c.) functions is proposed. Convergence to a global solution of the problem is proven and extensive computational experience with an implementation of the procedure is reported for up to 100,000 points. The procedure is also extended to solve conditional and limited distance location problems. We report on limited computational experiments on these extensions.
    Type of Medium: Electronic Resource
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  • 10
    ISSN: 1573-2916
    Keywords: Minimum concave cost network flow ; fixed number of sources and nonlinear arc costs ; strongly polynomial algorithm, parametric method
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract We prove that the Minimum Concave Cost Network Flow Problem with fixed numbers of sources and nonlinear arc costs can be solved by an algorithm requiring a number of elementary operations and a number of evaluations of the nonlinear cost functions which are both bounded by polynomials inr, n, m, wherer is the number of nodes,n is the number of arcs andm the number of sinks in the network.
    Type of Medium: Electronic Resource
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