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<item>
  <id>05674552</id>
  <dt>j</dt>
  <an>05674552</an>
  <augroup>
    <au>Achtziger, Wolfgang</au>
    <au>Stolpe, Mathias</au>
  </augroup>
  <ti>Global optimization of truss topology with discrete bar areas. II: Implementation and numerical results.</ti>
  <so>Comput. Optim. Appl. 44, No. 2, 315-341 (2009).</so>
  <py>2009</py>
  <pu>Springer, Norwell, MA</pu>
  <lagroup>
    <la>EN</la>
  </lagroup>
  <ccgroup>
  </ccgroup>
  <utgroup>
    <ut>truss topology optimization</ut>
    <ut>global optimization</ut>
    <ut>branch-and-bound</ut>
  </utgroup>
  <cigroup>
    <ci>Zbl 1181.90202</ci>
  </cigroup>
  <ligroup>
    <li>doi:10.1007/s10589-007-9152-7</li>
  </ligroup>
  <abgroup>
    <ab>Summary: A classical problem within the field of structural optimization is to find the stiffest truss design subject to a given external static load and a bound on the total volume. The design variables describe the cross sectional areas of the bars. This class of problems is well-studied for continuous bar areas. We consider here the difficult situation that the truss must be built from pre-produced bars with given areas. This paper together with Part I [ibid. 40, No.~2, 247--280 (2008; Zbl 1181.90202)] proposes an algorithmic framework for the calculation of a global optimizer of the underlying non-convex mixed integer design problem. In this paper we use the theory developed in Part I to design a convergent nonlinear branch-and-bound method tailored to solve large-scale instances of the original discrete problem. The problem formulation and the needed theoretical results from Part I are repeated such that this paper is self-contained. We focus on the implementation details but also establish finite convergence of the branch-and-bound method. The algorithm is based on solving a sequence of continuous non-convex relaxations which can be formulated as quadratic programs according to the theory in Part I. The quadratic programs to be treated within the branch-and-bound search all have the same feasible set and differ from each other only in the objective function. This is one reason for making the resulting branch-and-bound method very efficient. The paper closes with several large-scale numerical examples. These examples are, to the knowledge of the authors, by far the largest discrete topology design problems solved by means of global optimization.</ab>
    <rv></rv>
  </abgroup>
</item>