向前变椭圆 发表于 2025-3-23 11:50:21
https://doi.org/10.1007/978-3-319-95861-3thod for derivative-free optimization. We present different formulations for the surrogate problem considered at each search step of the Mesh Adaptive Direct Search (MADS) algorithm using a surrogate management framework. The proposed formulations are tested on two simulation-based multidisciplinaryintrude 发表于 2025-3-23 15:00:36
http://reply.papertrans.cn/32/3110/310996/310996_12.pnggnarled 发表于 2025-3-23 20:20:13
Simulation Optimization of Car-Following Models Using Flexible Techniques,improved methodological framework is suggested for the optimization of car-following models. Machine learning techniques, such as classification, locally weighted regression (loess) and clustering, are innovatively integrated. In this chapter, validation of the proposed methods is demonstrated on da百科全书 发表于 2025-3-23 23:09:20
http://reply.papertrans.cn/32/3110/310996/310996_14.png喊叫 发表于 2025-3-24 04:13:39
http://reply.papertrans.cn/32/3110/310996/310996_15.png打谷工具 发表于 2025-3-24 10:08:10
Design of Tuned Mass Dampers via Harmony Search for Different Optimization Objectives of Structurese on both displacements and accelerations. But for acceleration objective, a small benefit for accelerations can be seen although the optimum mass of TMD is very heavy according to displacement objective.宣称 发表于 2025-3-24 14:27:06
http://reply.papertrans.cn/32/3110/310996/310996_17.png内疚 发表于 2025-3-24 17:51:05
Hierarchical Topology Optimization for Bone Tissue Scaffold: Preliminary Results on the Design of alogy of each pore of the scaffold. In the first stage, an optimal material distribution is obtained to generate a stiffness match between implant and bone tissue. In the second stage, the optimal relative density distribution is used to interpolate target material properties at each location of theanarchist 发表于 2025-3-24 19:08:38
http://reply.papertrans.cn/32/3110/310996/310996_19.png意见一致 发表于 2025-3-24 23:59:42
Blackbox Optimization in Engineering Design: Adaptive Statistical Surrogates and Direct Search Algothod for derivative-free optimization. We present different formulations for the surrogate problem considered at each search step of the Mesh Adaptive Direct Search (MADS) algorithm using a surrogate management framework. The proposed formulations are tested on two simulation-based multidisciplinary