|
|
| |
| 基于成功历史参数自适应海星优化算法的多目标桁架结构优化设计 |
| Success History Parameter Self-adaptive Starfish Optimization Algorithm for Multi-objective Truss Structural Optimization Design |
| 投稿时间：2025-01-20 修订日期：2025-02-28 |
| DOI： |
| 中文关键词: 海星优化算法 多目标 成功历史参数自适应机制 差分进化算法 桁架结构优化 |
| 英文关键词:Starfish Optimization Algorithm Multi-objective Success-History-Based Parameter Adaptation Differential Evolution Algorithm Truss Structure Optimization |
| 基金项目:国家自然科学基金(12402139；52368070)；全国重点实验室开放课题(GZ24107)；海南省自然科学基金(5240N223)；国家重点研发计划(2022YFC3005304) |
|
| 摘要点击次数: 38 |
| 全文下载次数: 0 |
| 中文摘要: |
| 针对海星优化算法(SFOA)在多目标桁架结构优化中的应用，本文提出了一种基于成功历史参数自适应差分进化算法(SHADE)与海星优化算法的混合多目标优化算法——SHAMODE-SFOA。所提算法通过外部存档来保存和更新帕累托前沿, 并将海星优化算法的五维/单维搜索模式、捕食优化策略与基于成功历史参数自适应差分进化算法的更新机制相结合，来提升种群更新效率。所提算法采用200杆平面桁架和942杆空间桁架进行验证，并选取四种多目标智能优化算法进行对比。结果表明，SHAMODE-SFOA 算法在超体积、世代距离和间距与范围比值指标上表现最优，并获得较好的帕累托前沿分布，可为多目标结构优化设计提供新的解决方案。 |
| 英文摘要: |
| Aiming at the application of Starfish Optimization Algorithm (SFOA) in multi-objective truss structural optimization, this paper proposed a hybrid multi-objective success history-based parameter adaptive differential evolution (SHADE) with SFOA, called SHAMODE-SFOA. The proposed algorithm saves and updates the Pareto front through external archiving, and combines SFOA's five-dimensional/single-dimensional search mode and predation optimization strategy with the SHADE update mechanism to improve population update efficiency. The proposed algorithm is verified by using 200 bar plane truss and 942 bar space truss, and is compared with four other multi-objective intelligent optimization algorithms. The results show that SHAMODE-SFOA algorithm has the best performance on HV, GD and STE, with well-distributed Pareto fronts, which provides a new solution for multi-objective structural optimization design. |
| 查看/发表评论 下载PDF阅读器 |
