Multi-Objective Optimization of a Segmented Lunar Wheel Concept

2011 ◽  
Author(s):  
Michele Faragalli ◽  
Damiano Pasini ◽  
Peter Radzizsewski
Keyword(s):  
Optimization Problem ◽  
Element Model ◽  
Multi Objective Optimization ◽  
Stress Concentrations ◽  
Multi Objective ◽  
Optimization Framework ◽  
Multi Objective Genetic Algorithm ◽  
Design Variables ◽  
Rider Comfort ◽  
Original Concept

The goal of this work is to develop a systematic method for optimizing the structural design of a segmented wheel concept to improve its operating performance. In this study, a wheel concept is parameterized into a set of size and shape design variables, and a finite element model of the wheel component is created. A multi-objective optimization problem is formulated to optimize its directional compliance and reduce stress concentrations, which has a direct affect on the efficiency, traction, rider comfort, maneuverability, and reliability of the wheel. To solve the optimization problem, a Matlab-FE simulation loop is built and a multi-objective genetic algorithm is used to find the Pareto front of optimal solutions. A trade-off design is selected which demonstrates an improvement from the original concept. Finally, recommendations will be made to apply the structural optimization framework to alternative wheel conceptual designs.

scholarly journals Braille Block Detection via Multi-Objective Optimization from an Egocentric Viewpoint

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2775
Author(s):  
Tsubasa Takano ◽  
Takumi Nakane ◽  
Takuya Akashi ◽  
Chao Zhang
Keyword(s):  
Optimization Problem ◽  
Line Pair ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Optimization Framework ◽  
Visually Impaired People ◽  
Comprehensive Comparison ◽  
Basic Characteristics ◽  
Support Devices

In this paper, we propose a method to detect Braille blocks from an egocentric viewpoint, which is a key part of many walking support devices for visually impaired people. Our main contribution is to cast this task as a multi-objective optimization problem and exploits both the geometric and the appearance features for detection. Specifically, two objective functions were designed under an evolutionary optimization framework with a line pair modeled as an individual (i.e., solution). Both of the objectives follow the basic characteristics of the Braille blocks, which aim to clarify the boundaries and estimate the likelihood of the Braille block surface. Our proposed method was assessed by an originally collected and annotated dataset under real scenarios. Both quantitative and qualitative experimental results show that the proposed method can detect Braille blocks under various environments. We also provide a comprehensive comparison of the detection performance with respect to different multi-objective optimization algorithms.

An Improved Constrained Optimization Multi-Objective Genetic Algorithm and its Application in Engineering

2014 ◽  
Vol 962-965 ◽  
pp. 2903-2908
Author(s):  
Yun Lian Liu ◽  
Wen Li ◽  
Tie Bin Wu ◽  
Yun Cheng ◽  
Tao Yun Zhou ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Constrained Optimization ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Crossover Operator ◽  
Multi Objective Optimization ◽  
Constrained Optimization Problem ◽  
Great Ability ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm

An improved multi-objective genetic algorithm is proposed to solve constrained optimization problems. The constrained optimization problem is converted into a multi-objective optimization problem. In the evolution process, our algorithm is based on multi-objective technique, where the population is divided into dominated and non-dominated subpopulation. Arithmetic crossover operator is utilized for the randomly selected individuals from dominated and non-dominated subpopulation, respectively. The crossover operator can lead gradually the individuals to the extreme point and improve the local searching ability. Diversity mutation operator is introduced for non-dominated subpopulation. Through testing the performance of the proposed algorithm on 3 benchmark functions and 1 engineering optimization problems, and comparing with other meta-heuristics, the result of simulation shows that the proposed algorithm has great ability of global search. Keywords: multi-objective optimization;genetic algorithm;constrained optimization problem;engineering application

Cognitive Radio Decision Engine Based on Multi-Objective Genetic Algorithm

2011 ◽  
Vol 48-49 ◽  
pp. 314-317
Author(s):  
Di Wu ◽  
Sheng Yao Yang ◽  
J.C. Liu
Keyword(s):  
Genetic Algorithm ◽  
Cognitive Radio ◽  
Performance Optimization ◽  
Optimization Problem ◽  
Simulation Analysis ◽  
Multi Objective Optimization ◽  
Weighting Method ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Decision Engine

The performance optimization of cognitive radio is a multi-objective optimization problem. Existing genetic algorithms are difficult to assign the weight of each objective when the linear weighting method is used to simplify the multi-objective optimization problem into a single objective optimization problem. In this paper, we propose a new cognitive decision engine algorithm using multi-objective genetic algorithm with population adaptation. A multicarrier system is used for simulation analysis, and experimental results show that the proposed algorithm is effective and meets the real-time requirement.

A Multi-Objective Optimization Genetic Algorithm for SOPC Hardware-Software Partitioning

2012 ◽  
Vol 457-458 ◽  
pp. 1142-1148
Author(s):  
Fu Yang ◽  
Liu Xin ◽  
Pei Yuan Guo
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problem ◽  
Search Algorithm ◽  
Multi Objective Optimization ◽  
Key Technology ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Partitioning Problem ◽  
System On Programmable Chip ◽  
Software Partitioning

Hardware-software partitioning is the key technology in hardware-software co-design; the results will determine the design of system directly. Genetic algorithm is a classical search algorithm for solving such combinatorial optimization problem. A Multi-objective genetic algorithm for hardware-software partitioning is presented in this paper. This method can give consideration to both system performance and indicators such as time, power, area and cost, and achieve multi-objective optimization in system on programmable chip (SOPC). Simulation results show that the method can solve the SOPC hardware-software partitioning problem effectively.

Some Preliminary Results on the Development and Comparison of a New Multi-Objective Genetic Algorithm

2001 ◽  
Author(s):  
A. Farhang-Mehr ◽  
J. Wu ◽  
S. Azarm
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problem ◽  
Quality Metrics ◽  
Initial Population ◽  
Multi Objective Optimization ◽  
Pareto Solutions ◽  
Preliminary Results ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Speed Reducer

Abstract Some preliminary results for a new multi-objective genetic algorithm (MOGA) are presented. This new algorithm aims at obtaining the fullest possible representation of observed Pareto solutions to a multi-objective optimization problem. The algorithm, hereafter called entropy-based MOGA (or E-MOGA), is based on an application of the concepts from the statistical theory of gases to a MOGA. A few set quality metrics are introduced and used for a comparison of the E-MOGA to a previously published MOGA. Due to the stochastic nature of the MOGA, confidence intervals with a 95% confidence level are calculated for the quality metrics based on the randomness in the initial population. An engineering example, namely the design of a speed reducer is used to demonstrate the performance of E-MOGA when compared to the previous MOGA.

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.

scholarly journals Fuzzy set based multi-objective optimization for eight-rod mechanism via sensitivity analysis

2017 ◽  
Vol 233 (2) ◽  
pp. 333-343 ◽  
Author(s):  
Yongjun Pan ◽  
Chao Zhang ◽  
Banghui Yin ◽  
Baohua Wang
Keyword(s):  
Sensitivity Analysis ◽  
Membership Function ◽  
Fuzzy Set ◽  
Optimization Problem ◽  
Optimization Procedure ◽  
Multi Objective Optimization ◽  
Wheel Loader ◽  
Multi Objective ◽  
Design Variables ◽  
Working Device

The wheel loader multi-rod mechanism working device, which can be considered as a rigid multibody system, is a crucial component for shoveling and loading material. The six-rod and eight-rod mechanisms are two popular working devices used in construction, mining and agriculture. However, the design of the eight-rod mechanism device has not received much more attention due to its emerging applications. In this paper, a fuzzy set based multi-objective optimization procedure for an eight-rod mechanism device is presented by taking advantage of design sensitivities. The sensitivity analysis is carried out to extract the several most relevant design variables so as to simplify the optimization problem. Furthermore, the fuzzy set theory is introduced to express each objective in terms of membership function, thus different objectives can be measured in the same dimension. As a result, the multi-objective optimization problem is converted into a single objective through the combined membership function. Finally, an eight-rod mechanism working device of a wheel loader is analyzed and optimized by using the proposed method. The results show that the optimal eight-rod mechanism can provide a better kinematic performance.

Integrated Optimization of ACLD Treatment for Shape Control of Flexible Beams Using Multi-Objective Genetic Algorithm

Aerospace ◽  
2003 ◽  
Author(s):  
L. C. Hau ◽  
Eric H. K. Fung
Keyword(s):  
Genetic Algorithm ◽  
Shape Control ◽  
Optimization Problem ◽  
Viscoelastic Layer ◽  
Flexible Beams ◽  
Pareto Solution ◽  
Integrated Optimization ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Design Variables

This paper presents the use of multi-objective genetic algorithm (MOGA) to solve an integrated optimization problem for the shape control of flexible beams with Active Constrained Layer Damping (ACLD) treatment. The design objectives are to minimize the total weight of the system, the input voltage and the steady-state error between the achieved and desired shapes. Design variables include the thickness of the constraining layer and viscoelastic layer, the length and location of the ACLD patches, as well as the control gains. In order to evaluate the effect of different combinations of design variables on the system performance, the finite element method, in conjunction with the Golla-Hughes-McTavish (GHM) method, is employed to model a clamped-free beam with ACLD patches. As a result of the optimization, a Pareto solution is successfully obtained. It is shown that the MOGA is applicable to the present integrated optimization problem, and ACLD treatment is suitable for shape control of flexible structures.

Multi-Objective Optimization of Internal Compartment Layout of Oil Tankers

2019 ◽  
Vol 35 (4) ◽  
pp. 374-385 ◽  
Author(s):  
Hamidreza Jafaryeganeh ◽  
Manuel Ventura ◽  
Carlos Guedes Soares
Keyword(s):  
Bending Moment ◽  
Economic Benefits ◽  
Multi Objective Optimization ◽  
Safety Requirements ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Design Variables ◽  
Longitudinal Bending ◽  
Cargo Capacity ◽  
Oil Tankers

This work deals with the design of the internal layout of a shuttle tanker formulated as a multi-objective optimization problem, balancing cargo capacity and minimizing still water bending moment with safety requirements, in particular survivability after damage. A parametric model is used to specify the internal layout of a tanker ship considering a fixed hull shape and regulatory framework. The design variables include positions of watertight members in the internal layout, such as watertight bulkhead position, double-bottom height, and wing tanks width. Merit functions are the minimization of oil outflow parameter, maximization of cargo capacity, and minimization of the longitudinal bending moment, which are, respectively, represented for reduction of environmental pollution due to damaged oil tankers, improvement of economic benefits, and safety during operation. The multi-objective genetic algorithm is used for approaching the Pareto frontiers, and the choices between the optimal designs are discussed while introducing a utility function.

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.

Sign in / Sign up

Export Citation Format

Share Document