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ITERATION COMPLEXITY OF THE ALTERNATING DIRECTION METHOD OF MULTIPLIERS FOR QUASI-SEPARABLE PROBLEMS IN MULTI-DISCIPLINARY DESIGN OPTIMIZATION

机译:多学科设计优化中拟可分问题的乘积交替方向的迭代复杂性

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摘要

The Alternating Direction Method of Multipliers (ADMM) is a distributed algorithm suitable for quasi-separable problems in Multi-disciplinary Design Optimization. Previous authors have studied the convergence and complexity of the ADMM algorithm by treating it as an instance of the proximal point algorithm. In this paper, those previous results are extended to an alternate form of the ADMM algorithm applied to the quasi-separable problem. Secondly, a dynamic penalty parameter updating heuristic for the ADMM algorithm is introduced and compared against a previously proposed updating heuristic. The proposed updating heuristic was tested on a distributed linear model fitting example and performed favorably against the other heuristic and the fixed penalty parameter scheme.
机译:乘数交替方向法(ADMM)是一种分布式算法,适用于多学科设计优化中的准可分离问题。以前的作者通过将ADMM算法作为近端算法的一个实例来研究其收敛性和复杂性。在本文中,这些先前的结果扩展为应用于准可分问题的ADMM算法的另一种形式。其次,介绍了针对ADMM算法的动态惩罚参数更新启发式算法,并将其与先前提出的更新启发式算法进行了比较。建议的更新启发式算法在分布式线性模型拟合示例上进行了测试,与其他启发式算法和固定惩罚参数方案相比,表现出色。

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