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Bayes approach to solving TEAM benchmark problems 22 and 25 and its comparison with other optimization techniques

机译:贝叶斯致求团队基准问题22和25的方法及其与其他优化技术的比较

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The Bayes approach is used for solution of benchmark problems 22 and 25. The main purpose of the paper is to evaluate its applicability for solving complex technical problems (up to now, this technique was only very rarely used in the domain of such tasks). The parameters of this approach are compared with characteristics of several other heuristic and deterministic optimization techniques implemented in commercial code COMSOL Multi-physics and own open-source application Agros Suite. The results confirm that the Bayes approach is superior in a number of aspects and for the solution of real-life tasks it represents a powerful and prospective alternative to existing optimization methods (C) 2017 Elsevier Inc. All rights reserved.
机译:贝叶斯方法用于解决基准问题22和25.本文的主要目的是评估其对解决复杂技术问题的适用性(至今,该技术仅在此类任务的领域中非常易于使用)。 这种方法的参数与在商业代码COMSOL多物理和自己的开源应用程序AGOROS套件中实现的其他一些启发式和确定性优化技术的特征。 结果证实,贝叶斯方法在许多方面都是优越的,并且对于现实生活任务的解决方案,它代表了现有优化方法(C)2017 Elsevier Inc.保留的所有权利的强大和预期替代方案。

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