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Performance of the Whale Optimization Algorithm in Space Steel Frame Optimization Problems

机译:空间钢框优化问题中鲸井优化算法的性能

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Frame optimization that contains highly non-linear and irregular functions and discrete design variables is one of the most challenging optimization problems. Therefore, gradient-based optimization techniques cannot be successful in such problems. Metaheuristic techniques, especially population-based metaheuristic techniques, perform highly effective in solving the frame optimization problem. However, stochastic processes' performances included in metaheuristic techniques vary based on the problem. Accordingly, researches on the performance of novel metaheuristic techniques on challenging engineering problems continue. One of the novel metaheuristic techniques is the whale optimization algorithm (WOA) which is inspired by the bubble-net feeding behavior of humpback whales. The aim of this study is testing the performance of WOA for space steel frame optimization problems. For this purpose, WOA-cased frame optimization program will be developed. Benchmark frame structures are selected to compare optimum solutions with literature results.
机译:包含高度非线性和不规则功能和离散设计变量的帧优化是最具挑战性的优化问题之一。因此,基于梯度的优化技术在这些问题中不能成功。常规技术,尤其是基于人口的成群质技术,在解决帧优化问题方面表现出高度有效。然而,包括在地培技术中的随机过程的性能因问题而异。因此,对挑战工程问题的新型成群质技术的性能研究继续研究。其中一种新型的成式技术是鲸料优化算法(WOA),其受到驼背鲸的泡净馈送行为的启发。本研究的目的正在测试WOA对空间钢框优化问题的性能。为此目的,将开发WOA-Cased帧优化程序。选择基准框架结构以比较具有文献结果的最佳解决方案。

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