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IMPROVED REGULARITY ASSUMPTIONS FOR PARTIAL OUTER CONVEXIFICATION OF MIXED-INTEGER PDE-CONSTRAINED OPTIMIZATION PROBLEMS

机译:改善混合整数PDE受限优化问题的部分外凸的规律性假设

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摘要

Partial outer convexification is a relaxation technique for MIOCPs being constrained by time-dependent differential equations. Sum-Up-Rounding algorithms allow to approximate feasible points of the relaxed, convexified continuous problem with binary ones that are feasible up to an arbitrarily small delta 0. We show that this approximation property holds for ODEs and semilinear PDEs under mild regularity assumptions on the nonlinearity and the solution trajectory of the PDE. In particular, requirements of differentiability and uniformly bounded derivatives on the involved functions from previous work are not necessary to show convergence of the method.
机译:部分外部凸起是由时间依赖性微分方程约束的Miocps的弛豫技术。总结舍入算法允许近似的可行性点,与二元小三角形的二进制文件近似的凸出的连续问题。我们表明该近似特性在轻度规则的假设下保持杂散和半线性PDE PDE的非线性和溶液轨迹。特别地,对先前作品的涉及功能的可分利差和统一的衍生物的要求是不需要显示该方法的收敛性的。

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