Algorithms for Optimizing Systems with Multiple Extremum Functionals

Pub Date : 2024-04-22 DOI:10.1134/s0965542524030163
V. K. Tolstykh
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Abstract

The problem of minimizing (maximizing) multiple extremum functionals (infinite-dimensional optimization) is considered. This problem cannot be solved by conventional gradient methods. New gradient methods with adaptive relaxation of steps in the vicinity of local extrema are proposed. The efficiency of the proposed methods is demonstrated by the example of optimizing the shape of a hydraulic gun nozzle with respect to the objective functional, which is the average force of the hydraulic pulse jet momentum acting on an obstacle. Two local maxima are found, the second of which is global; in the second maximum, the average force of the jet momentum is three times higher than in the first maximum. The corresponding nozzle shape is optimal. Conventional gradient methods have not found any maximum; i.e., they were unable to solve the problem.

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优化具有多个极值函数的系统的算法
摘要 研究了多重极值函数的最小化(最大化)问题(无穷维优化)。传统的梯度方法无法解决这一问题。本文提出了在局部极值附近自适应放宽步长的新梯度方法。以优化液压喷枪喷嘴的形状为例,证明了所提方法的效率,其目标函数是作用在障碍物上的液压脉冲喷射动量的平均力。发现了两个局部最大值,其中第二个是全局最大值;在第二个最大值中,喷射动量的平均力是第一个最大值的三倍。相应的喷嘴形状是最佳的。传统的梯度方法没有发现任何最大值,也就是说,它们无法解决这个问题。
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