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Global optimization of generalized semi-infinite programs using disjunctive programming

机译:使用析取规划的广义半无限程序的全局优化

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We propose a new branch-and-bound algorithm for global minimization of box-constrained generalized semi-infinite programs. It treats the inherent disjunctive structure of these problems by tailored lower bounding procedures. Three different possibilities are examined. The first one relies on standard lower bounding procedures from conjunctive global optimization as described in Kirst et al. (J Global Optim 69: 283-307, 2017). The second and the third alternative are based on linearization techniques by which we derive linear disjunctive relaxations of the considered sub-problems. Solving these by either mixed-integer linear reformulations or, alternatively, by disjunctive linear programming techniques yields two additional possibilities. Our numerical results on standard test problems with these three lower bounding procedures show the merits of our approach.
机译:我们为框约束的广义半无限程序的全局最小化提出了一种新的分支定界算法。它通过量身定制的下限程序来处理这些问题的固有分离结构。研究了三种不同的可能性。第一个依赖于全局联合优化的标准下界过程,如Kirst等人所述。 (J Global Optim 69:283-307,2017)。第二和第三种选择基于线性化技术,通过这些技术,我们可以得出所考虑子问题的线性析取松弛。通过混合整数线性重构或通过析取线性编程技术来解决这些问题,会产生另外两种可能性。我们使用这三个下限程序对标准测试问题进行的数值结果表明了我们方法的优点。

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