scholarly journals A Multi-Objective Optimization Approach Using Genetic Algorithms for Quick Response to Effects of Variability in Flow Manufacturing

2012 ◽  
Vol 3 (9) ◽  
Author(s):  
Riham Khalil ◽  
David Stockton ◽  
Parminder Singh ◽  
Lawrence Manyonge
Keyword(s):  
Genetic Algorithms ◽  
Optimization Approach ◽  
Quick Response ◽  
Multi Objective Optimization ◽  
Multi Objective

scholarly journals Design of low-power CMOS VLSI circuits using multi-objective optimization in genetic algorithms

2021 ◽  
Vol 12 (1) ◽  
pp. 215-224
Author(s):  
Mahnoor Maghroori ◽  
Mehdi Dolatshahi
Keyword(s):  
Genetic Algorithms ◽  
Integrated Circuits ◽  
Circuit Simulation ◽  
Cmos Technology ◽  
Vlsi Circuits ◽  
Design Tool ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Cmos Vlsi

This paper presents a design CAD tool for automated design of digital CMOS VLSI circuits. In order to fit the circuit performance into desired specifications, a multi-objective optimization approach based on genetic algorithms (GA) is proposed and the transistor sizes are calculated based on the analytical equations describing the behavior of the circuit. The optimization algorithm is developed in MATLAB and the performance of the designed circuit is verified using HSPICE simulations based on 0.18µm CMOS technology parameters. Different digital integrated circuits were successfully designed and verified using the proposed design tool. It is also shown in this paper that, the design results obtained from the proposed algorithm in MATLAB, have a very good agreement with the obtained circuit simulation results in HSPICE.

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.

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