A multi-objective optimization algorithm for feature selection problems

2021 ◽  
Author(s):  
Benyamin Abdollahzadeh ◽  
Farhad Soleimanian Gharehchopogh
Keyword(s):  
Feature Selection ◽  
Optimization Algorithm ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Selection Problems

scholarly journals Multi-Objective Multidisciplinary Design Optimization of a Robotic Fish System

2021 ◽  
Vol 9 (5) ◽  
pp. 478
Author(s):  
Hao Chen ◽  
Weikun Li ◽  
Weicheng Cui ◽  
Ping Yang ◽  
Linke Chen
Keyword(s):  
Design Optimization ◽  
Optimization Algorithm ◽  
Multidisciplinary Design Optimization ◽  
Robotic Fish ◽  
Multidisciplinary Design ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Cfd Method ◽  
The Individual

Biomimetic robotic fish systems have attracted huge attention due to the advantages of flexibility and adaptability. They are typically complex systems that involve many disciplines. The design of robotic fish is a multi-objective multidisciplinary design optimization problem. However, the research on the design optimization of robotic fish is rare. In this paper, by combining an efficient multidisciplinary design optimization approach and a novel multi-objective optimization algorithm, a multi-objective multidisciplinary design optimization (MMDO) strategy named IDF-DMOEOA is proposed for the conceptual design of a three-joint robotic fish system. In the proposed IDF-DMOEOA strategy, the individual discipline feasible (IDF) approach is adopted. A novel multi-objective optimization algorithm, disruption-based multi-objective equilibrium optimization algorithm (DMOEOA), is utilized as the optimizer. The proposed MMDO strategy is first applied to the design optimization of the robotic fish system, and the robotic fish system is decomposed into four disciplines: hydrodynamics, propulsion, weight and equilibrium, and energy. The computational fluid dynamics (CFD) method is employed to predict the robotic fish’s hydrodynamics characteristics, and the backpropagation neural network is adopted as the surrogate model to reduce the CFD method’s computational expense. The optimization results indicate that the optimized robotic fish shows better performance than the initial design, proving the proposed IDF-DMOEOA strategy’s effectiveness.

scholarly journals An effective docking strategy for virtual screening based on multi-objective optimization algorithm

2009 ◽  
Vol 10 (1) ◽  
Author(s):  
Honglin Li ◽  
Hailei Zhang ◽  
Mingyue Zheng ◽  
Jie Luo ◽  
Ling Kang ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Optimization Algorithm ◽  
Multi Objective Optimization ◽  
Multi Objective
Sign in / Sign up

Export Citation Format

Share Document