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A local approximation based multi-objective optimization algorithm with applications

机译:基于局部逼近的多目标优化算法及其应用

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摘要

Optimization techniques are useful tools to the design of complex systems. Especially in case of multiple conflicting performance indexes, the knowledge of the tradeoffs by means of Pareto optimality can help the designer to achieve the best solution. Due to the increasing power of the computing tools, more and more accurate and time consuming models are used. In this case, the Pareto set computation can be a hard task (the Pareto set can be nonconvex, nonlinearities and discontinuities can occur) and the efficiency and the accuracy become crucial features for an optimization algorithm. In this paper an optimization algorithm based on local approximation of the objective and constraints functions is presented and tested with some well known test functions. The optimal design of the suspension system of a ground vehicle is performed by the new algorithm in order to reach the best tradeoff by means of road holding, comfort, working space and cornering behavior. The numerical results show that the proposed algorithm has good accuracy and high efficiency if compared to some widely used methods. The results are explained providing some general observations on the efficiency of local approximation based algorithm an other well known algorithms.
机译:优化技术是设计复杂系统的有用工具。特别是在多个性能指标冲突的情况下,借助帕累托最优性进行权衡的知识可以帮助设计人员获得最佳解决方案。由于计算工具的功能不断增强,因此使用了越来越多的准确和费时的模型。在这种情况下,帕累托集计算可能是一项艰巨的任务(帕累托集可以是非凸的,可能会出现非线性和不连续性),而效率和准确性成为优化算法的关键特征。本文提出了一种基于目标函数和约束函数的局部逼近的优化算法,并使用一些众所周知的测试函数对其进行了测试。新算法对地面车辆的悬架系统进行了优化设计,以便通过抓地力,舒适性,工作空间和转弯性能达到最佳平衡。数值结果表明,与一些广泛使用的方法相比,该算法具有良好的精度和较高的效率。解释了结果,提供了有关基于局部逼近的算法和其他知名算法的效率的一些一般性观察。

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