Applications of Multiple Objective Genetic Algorithms in the Optimization Design of Tracked Self-Moving Power’s Layout

2013 ◽  
Vol 307 ◽  
pp. 161-165
Author(s):  
Hai Jin ◽  
Jin Fa Xie
Keyword(s):  
Optimization Design ◽  
Pareto Front ◽  
Layout Optimization ◽  
Multiple Objective ◽  
Multi Objective Optimization ◽  
Layout Problem ◽  
Basic Principles ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Set Up

A multi-objective genetic algorithm is applied into the layout optimization of tracked self-moving power. The layout optimization mathematical model was set up. Then introduced the basic principles of NSGA-Ⅱ, which is a Pareto multi-objective optimization algorithm. Finally, NSGA-Ⅱwas presented to solve the layout problem. The algorithm was proved to be effective by some practical examples. The results showed that the algorithm can spread toward the whole Pareto front, and provide many reasonable solutions once for all.

scholarly journals Multi-Objective Optimization Design of an Electrohydrostatic Actuator Based on a Particle Swarm Optimization Algorithm and an Analytic Hierarchy Process

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2426 ◽  
Author(s):  
Bo Yu ◽  
Shuai Wu ◽  
Zongxia Jiao ◽  
Yaoxing Shang
Keyword(s):  
Particle Swarm Optimization ◽  
Power Consumption ◽  
Analytic Hierarchy Process ◽  
Optimization Design ◽  
Pareto Front ◽  
Multi Objective Optimization ◽  
Analytic Hierarchy ◽  
Swarm Optimization ◽  
Multi Objective ◽  
Hierarchy Process

During the last few years, the concept of more-electric aircraft has been pushed ahead by industry and academics. For a more-electric actuation system, the electrohydrostatic actuator (EHA) has shown its potential for better reliability, low maintenance cost and reducing aircraft weight. Designing an EHA for aviation applications is a hard task, which should balance several inconsistent objectives simultaneously, such as weight, stiffness and power consumption. This work presents a method to obtain the optimal EHA, which combines multi-objective optimization with a synthetic decision method, that is, a multi-objective optimization design method, that can combine designers’ preferences and experiences. The evaluation model of an EHA in terms of weight, stiffness and power consumption is studied in the first section. Then, a multi-objective particle swarm optimization (MOPSO) algorithm is introduced to obtain the Pareto front, and an analytic hierarchy process (AHP) is applied to help find the optimal design in the Pareto front. A demo of an EHA design illustrates the feasibility of the proposed method.

scholarly journals A Smart-Distributed Pareto Front Using the ev-MOGA Evolutionary Algorithm

2014 ◽  
Vol 23 (02) ◽  
pp. 1450002 ◽  
Author(s):  
J. M. Herrero ◽  
G. Reynoso-Meza ◽  
M. Martínez ◽  
X. Blasco ◽  
J. Sanchis
Keyword(s):  
Pareto Front ◽  
Optimization Methods ◽  
Optimization Method ◽  
Initial Condition ◽  
Multi Objective Optimization ◽  
Computational Burden ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Normalized Normal Constraint ◽  
Normal Constraint

Obtaining multi-objective optimization solutions with a small number of points smartly distributed along the Pareto front is a challenge. Optimization methods, such as the normalized normal constraint (NNC), propose the use of a filter to achieve a smart Pareto front distribution. The NCC optimization method presents several disadvantages related with the procedure itself, initial condition dependency, and computational burden. In this article, the epsilon-variable multi-objective genetic algorithm (ev-MOGA) is presented. This algorithm characterizes the Pareto front in a smart way and removes the disadvantages of the NNC method. Finally, examples of a three-bar truss design and controller tuning optimizations are presented for comparison purposes.

Automobile Active Suspension System Optimization Design Based on Modified Multi-Objective Genetic Algorithm

2012 ◽  
Vol 157-158 ◽  
pp. 1515-1518 ◽  
Author(s):  
Yi Zhang ◽  
Chao Lu ◽  
Hu Zhang
Keyword(s):  
Objective Function ◽  
High Dimension ◽  
Optimization Design ◽  
Single Point ◽  
Active Suspension ◽  
System Optimization ◽  
Suspension System ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Set Up

A dynamic model of automobile active suspension system is established, based on which a high dimension objective model for active suspension system is set up. And through linear combinations, high dimension multi-objective function is translated into a low dimension objective function. The modified NSGAII with single point compound crossover has been adopted to realize the optimization. In the paper, the performance active suspension system can realize integrated optimization. The results show that this way can effectively enhance effect of the automobile active suspension system.

Multi-Objective Optimization Design of Composite I-Beam Embedded with Viscoelastic Layers

2010 ◽  
Vol 156-157 ◽  
pp. 456-461
Author(s):  
Tao Wang ◽  
Song Lin ◽  
Bin Wu ◽  
Chao Xu
Keyword(s):  
Composite Structures ◽  
Optimization Design ◽  
Optimization Problems ◽  
Damping Capacity ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Beam Design ◽  
Design Variables ◽  
Viscoelastic Layers

Damping capacity and stiffness loss must be considered together in the design of integral damping composite structures. In the present paper, a discrete layer beam finite element is used to model and analyze a damped composite I-beam embedded with viscoelastic layers. Two multi-objective optimization models are developed with maximum natural frequency and modal loss factor. In the first model, only one damping layer is embedded in each flange of the I-beam. Design variables consist of damping layer thickness and its inserting location. In the second model, multiple damping layers of equal thickness are embedded in the flanges. Design variables included the number of damping layers and their inserting locations. Multi-objective genetic algorithm is used to solve optimization problems. It is showed that the analysis method has acceptable accuracy for composite damped I-beams, and it is convenient for optimization design of integral damping composite structures, especially for the cases embedded with multiple damping layers.

Multi-Objective Optimization of the FOFAS Based on the Workbench/Exploration

2014 ◽  
Vol 889-890 ◽  
pp. 101-106
Author(s):  
Liang Xiao ◽  
Ming Feng ◽  
Yang Ge ◽  
Wei Wang
Keyword(s):  
Optimization Design ◽  
Parametric Design ◽  
Focal Point ◽  
Equivalent Stress ◽  
Minimum Mass ◽  
Multi Objective Optimization ◽  
Pareto Solutions ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Optimization Simulation

A certain FOFAS (framework of feeding ammunition system) has extremely important function such as fixing, supporting and leading orientation, etc. Optimization design for FOFAS is the focal point under meeting such criterions as stiffness, strength and safety. Using Workbench, this article mainly carried out parametric design to optimize feeding ammunition box under Multi-objective Genetic Algorithm (MOGA). Pareto solutions from optimization simulation showed that minimum mass of ammunition box was decreased by 6.17%, displacement deformation had little influence on the FOFAS and equivalent stress was increased by 0.35%. The optimizing results satisfied the strength, stiffness and polynomial response requirements.

Multi-Objective Fuzzy Optimization Design of Truck Differential

2014 ◽  
Vol 722 ◽  
pp. 84-88
Author(s):  
Er Zhong An ◽  
Yun Chao Wang
Keyword(s):  
Optimization Design ◽  
Fuzzy Theory ◽  
Fuzzy Optimization ◽  
Multi Objective Optimization ◽  
Gear Teeth ◽  
Multi Objective ◽  
Section Modulus ◽  
Planet Gear ◽  
Fuzzy Solution ◽  
Set Up

Multi-objective optimization technology and Fuzzy theory were applied to design truck differential based on consideration on its force condition. The mathematical model for the multi-objective optimization design was set up under the objective of the minimum volume of the differential, maximal strength of planet gear, with the design variable of planet gear teeth number Z1, axle shaft gear teeth number Z2, section modulus ms and working width b. Then, the fuzzy solution of multi-objective optimization were use to solve the model. Practical example of calculation shows that, the fuzzy optimization result is superior to that of regular optimization and traditional design, differential volume deceased by 32.73% and 1.92% respectively. Comparing with nominal design, the load of planet gear increases 17%, but is far below its permissible value, and also reduced by 9.04% than that of regular optimization.

scholarly journals Research on Blank Optimization Design Based on Low-Carbon and Low-Cost Blank Process Route Optimization Model

2021 ◽  
Vol 13 (4) ◽  
pp. 1929
Author(s):  
Yongmao Xiao ◽  
Wei Yan ◽  
Ruping Wang ◽  
Zhigang Jiang ◽  
Ying Liu
Keyword(s):  
Optimization Model ◽  
Optimization Design ◽  
Design Method ◽  
Low Cost ◽  
Route Optimization ◽  
Low Carbon ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Blank Design ◽  
Process Route

The optimization of blank design is the key to the implementation of a green innovation strategy. The process of blank design determines more than 80% of resource consumption and environmental emissions during the blank processing. Unfortunately, the traditional blank design method based on function and quality is not suitable for today’s sustainable development concept. In order to solve this problem, a research method of blank design optimization based on a low-carbon and low-cost process route optimization is proposed. Aiming at the processing characteristics of complex box type blank parts, the concept of the workstep element is proposed to represent the characteristics of machining parts, a low-carbon and low-cost multi-objective optimization model is established, and relevant constraints are set up. In addition, an intelligent generation algorithm of a working step chain is proposed, and combined with a particle swarm optimization algorithm to solve the optimization model. Finally, the feasibility and practicability of the method are verified by taking the processing of the blank of an emulsion box as an example. The data comparison shows that the comprehensive performance of the low-carbon and low-cost multi-objective optimization is the best, which meets the requirements of low-carbon processing, low-cost, and sustainable production.

scholarly journals A Three-Dimensional Numerical and Multi-Objective Optimal Design of Wavy Plate-Fins Heat Exchangers

Processes ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 9
Author(s):  
Chao Yu ◽  
Xiangyao Xue ◽  
Kui Shi ◽  
Mingzhen Shao
Keyword(s):  
Heat Exchangers ◽  
Cfd Simulation ◽  
Three Dimensional ◽  
Basis Functions ◽  
Approximation Model ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Colburn Factor ◽  
Heat Exchange Efficiency

This paper presents a method for optimizing wavy plate-fin heat exchangers accurately and efficiently. It combines CFD simulation, Radical Basis Functions (RBF) with multi-objective optimization to improve the performance. The optimization of the Colburn factor j and the friction coefficient f is regarded as a multi-objective optimization problem, due to the existence of two contradictory goals. The approximation model was obtained by Radical Basis Functions, and the shape of the heat exchanger was optimized by multi-objective genetic algorithm (MOGA). The optimization results showed that j increased by 17.62% and f decreased by 20.76%, indicating that the heat exchange efficiency was significantly enhanced and the fluid structure resistance reduced. Then, from the aspects of field synergy and tubulence energy, the performance advantage of the optimized structure was further confirmed.

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