返回
Alpine skiing optimization: A new bio-inspired optimization algorithm
DOI:10.1016/j.advengsoft.2022.103158.png)
摘要
En 中文
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-ofthe-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.
Keyword:
Swarm intelligence
Alpine skiing optimization algorithm
Physical stamina
Constrained optimization
Auto drum fashioned brake
期刊
IF:
5.7
论文数:
3.4K
被引数:
1.2W
机构
引用论文
Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems布谷鸟搜索算法: 一种解决结构优化问题的元启发式方法
Hybridizing particle swarm optimization with differential evolution for constrained numerical and engineering optimization粒子群优化与差分进化混合用于约束数值和工程优化
Differential Evolution Algorithm With Strategy Adaptation for Global Numerical Optimization求解全局数值优化问题的策略自适应差分进化算法

