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Compare the Efficiencies of GA, RPSO, SA, DIRECT Global Optimization Methods 比较GA、RPSO、SA、DIRECT全局优化方法的效率
Pub Date : 2022-07-29 DOI: 10.1109/GTSD54989.2022.9989155
X. Lam
Design Optimization is research area which was carried out a lot in the world, with many applications in the specifications of mechanical engineering, aerospace engineering, civil engineering. The global optimization methods are more effective than local optimization methods. In this article, the authors will do new research about the efficiencies of GA, RPSO, SA, and DIRECT global optimization methods. It is investigated that RPSO is more accurate and more robust than GA and SA in terms of stochastic global optimization methods. RPSO usually requires a little bit less computational cost than SA, but RPSO requires very much more function calls than SA. SA is more accurate than GA, but SA requires more function calls than GA. Besides, DIRECT is also as accurate, robust as RPSO. DIRECT usually utilizes less computational cost than RPSO. DIRECT requires very much less function calls than RPSO. However, DIRECT is just a deterministic global optimization method, hence it requires some suggestions (hints) about minimal value of objective function, this is a weakness of this method. In summary, each method has its own strengths and weaknesses. The users should choose an appropriate method depending on their different purposes.
设计优化是国际上开展较多的研究领域,在机械工程、航空航天工程、土木工程等领域有着广泛的应用。全局优化方法比局部优化方法更有效。在本文中,作者将对GA、RPSO、SA和DIRECT全局优化方法的效率进行新的研究。研究了RPSO在随机全局寻优方面比GA和SA具有更高的精度和鲁棒性。RPSO通常需要比SA少一点的计算成本,但是RPSO需要比SA多得多的函数调用。SA比GA更精确,但是SA比GA需要更多的函数调用。此外,DIRECT也像RPSO一样准确、健壮。DIRECT通常比RPSO使用更少的计算成本。DIRECT比RPSO需要更少的函数调用。然而,DIRECT只是一种确定性全局优化方法,因此需要对目标函数的最小值进行一些建议(提示),这是该方法的一个缺点。总之,每种方法都有自己的优点和缺点。用户应根据自己的不同目的选择合适的方法。
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2022 6th International Conference on Green Technology and Sustainable Development (GTSD)
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