计算机科学
制动器
数学优化
优化算法
最优化问题
算法
元启发式
工程类
数学
机械工程
作者
Yongliang Yuan,Jianji Ren,Shuo Wang,Zhenxi Wang,Xiaokai Mu,Wu Zhao
标识
DOI:10.1016/j.advengsoft.2022.103158
摘要
A novel swarm intelligence optimization algorithm is proposed, which is named alpine skiing optimization (ASO). The main inspiration of the ASO originated from the behaviors of skiers competing for the championship. In the ASO, physical stamina and sprint are two essential factors for skiers to win the tournament, which are similar to the two stages of exploration and exploitation. The skiers revealed the behaviour of winning the tournament according to the static sliding and dynamic sliding. This work simulates this behaviour from a mathematical perspective and develops the ASO algorithm. The performance of the ASO algorithm is investigated, through a comparison with many competitive optimization algorithms and four constrained engineering problems. The statistical results validate that the ASO can provide competitive results compared to other state-of-the-art optimization algorithms. Furthermore, ASO is applied to optimize the parameter of an auto drum fashioned brake engineering problem. The objective function is chosen to maximize the braking efficiency coefficient. Results show that the braking efficiency factor is improved by 28.446% compared with the initial design.
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