On the Entropy of Multi-Objective Design Optimization Solution Sets

2002 ◽  
Author(s):  
Ali Farhang-Mehr ◽  
Shapour Azarm
Keyword(s):  
Design Optimization ◽  
Optimization Technique ◽  
Optimization Techniques ◽  
Pareto Optimal ◽  
Multi Objective Optimization ◽  
Solution Sets ◽  
Multi Objective ◽  
Speed Reducer ◽  
Quantitative Basis ◽  
Multiobjective Design

In this paper, an entropy-based metric is presented for quality assessment of non-dominated solution sets obtained from a multiobjective optimization technique. This metric quantifies the ‘goodness’ of a solution set in terms of its distribution quality over the Pareto-optimal frontier. Therefore, it can be useful in comparison studies of different multi-objective optimization techniques, such as Multi-Objective Genetic Algorithms (MOGAs), wherein the capabilities of such techniques to produce and maintain diversity among different solution points are desired to be compared on a quantitative basis. An engineering test example, the multiobjective design optimization of a speed-reducer, is presented in order to demonstrate an application of the proposed entropy metric.

An Information-Theoretic Entropy Metric for Assessing Multi-Objective Optimization Solution Set Quality

2003 ◽  
Vol 125 (4) ◽  
pp. 655-663 ◽  
Author(s):  
Ali Farhang-Mehr ◽  
Shapour Azarm
Keyword(s):  
Evolutionary Algorithms ◽  
Pareto Frontier ◽  
Optimization Techniques ◽  
Solution Set ◽  
Multi Objective Optimization ◽  
Information Theoretic ◽  
Multi Objective ◽  
Speed Reducer ◽  
Quantitative Basis

An entropy-based metric is presented that can be used for assessing the quality of a solution set as obtained from multi-objective optimization techniques. This metric quantifies the “goodness” of a set of solutions in terms of distribution quality over the Pareto frontier. The metric can be used to compare the performance of different multi-objective optimization techniques. In particular, the metric can be used in analysis of multi-objective evolutionary algorithms, wherein the capabilities of such techniques to produce and maintain diversity among different solution points are desired to be compared on a quantitative basis. An engineering test example, the multi-objective design optimization of a speed-reducer, is provided to demonstrate an application of the proposed entropy metric.

The Multiobjective Design Optimization of pMUT Hydrophone

2015 ◽  
Vol 727-728 ◽  
pp. 660-665
Author(s):  
Shun Hsyung Chang ◽  
Fu Tai Wang ◽  
Jiing Kae Wu ◽  
Sergey N. Shevtsov ◽  
Igor V. Zhilyaev ◽  
...  
Keyword(s):  
Finite Element ◽  
Frequency Response ◽  
Design Optimization ◽  
Frequency Band ◽  
Vacuum Chamber ◽  
Fe Model ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Membrane Type ◽  
Multiobjective Design

The paper presents some results of multi-objective optimization for the multilayered membrane-type piezoceramic MEMS based transducers with perforated active PZT and intermediate diaphragms, covered by the protective plates, and a vacuum chamber. An influence of the protective plate elastic and viscous properties, the dimensions and the relative areas of the perforated holes on the sensitivity’s frequency response of the hydrophone was studied for the broadening and equalizes the operating frequency band. We optimize the key design’s parameters using the Pareto approach with the finite element (FE) model of coupled piezoelectric-acoustic problem for the hydrophone.

Application of multi-objective optimization techniques to improve the aerodynamic performance of a tunnel ventilation jet fan

2014 ◽  
Vol 229 (1) ◽  
pp. 91-105 ◽  
Author(s):  
Joon-Hyung Kim ◽  
Jin-Hyuk Kim ◽  
Joon-Yong Yoon ◽  
Young-Seok Choi ◽  
Sang-Ho Yang
Keyword(s):  
Objective Function ◽  
Design Optimization ◽  
Optimization Model ◽  
Forward Direction ◽  
Aerodynamic Performance ◽  
Optimization Techniques ◽  
Multi Objective Optimization ◽  
Tunnel Ventilation ◽  
Multi Objective ◽  
Jet Fan

This paper describes the design optimization of a tunnel ventilation jet fan through multi-objective optimization techniques. Four design variables were selected for design optimization. To analyze the performance of the fan, numerical analyses were conducted, and three-dimensional Reynolds-averaged Navier–Stokes equations with a shear stress transport turbulence model were solved. Two objective functions, the total efficiency of the forward direction and the ratio of the reverse direction outlet velocity to the forward direction outlet velocity, were employed, and multi-objective optimization was carried out to improve the aerodynamic performance. A response surface approximation surrogate model was constructed for each objective function based on numerical solutions obtained at specified design points. The non-dominated sorting genetic algorithm with a local search procedure was used for multi-objective optimization. The tradeoff between the two objectives was determined and described with respect to the Pareto-optimal solutions. Based on the analysis of the optimization results, we propose an optimization model to satisfy the objective function. Finally, to verify the performance, experiments with the base model and the optimization model were carried out.

Collaborative Optimization of Excavator Boom Mechanism Parameters under Multiple Loading Conditions

2013 ◽  
Vol 655-657 ◽  
pp. 390-395
Author(s):  
Guang Qiu Yin ◽  
Shu He Zheng ◽  
Shu Wen Lin
Keyword(s):  
Optimization Problems ◽  
Optimization Technique ◽  
Systems Design ◽  
Optimization Techniques ◽  
Collaborative Optimization ◽  
Multi Objective Optimization ◽  
Design And Optimization ◽  
Multi Objective ◽  
Coupling System ◽  
Multiple Loading

On the base of explaining Multi-Objective Optimization Problems (MOOP) and Collaborative Optimization Techniques (COT), this paper puts forward an original and efficient approach—Collaborative Optimization Technique for Multi-Objective Optimization Problems (COTMOOP)—which combines Collaborative Optimization (CO) techniques and Evolutionary Algorithms (EAs). It has been developed so as to facilitate the organizations and increase the performances of complex coupling systems design and optimization. The newly method has been succeeded in applying to the design and optimization of excavator boom mechanism that is a complex coupling system. The optimal solutions can prove that the approach is efficient and practical.

Multi-objective design optimization of a rotary compressor for household air-conditioning

2008 ◽  
Vol 222 (4) ◽  
pp. 241-250 ◽  
Author(s):  
K T Ooi ◽  
H Q Lee
Keyword(s):  
Design Optimization ◽  
Optimization Technique ◽  
Piston Compressor ◽  
Input Power ◽  
Coefficient Of Performance ◽  
Rotary Compressor ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Compressor Design ◽  
Optimum Solution

This paper presents a design optimization of a rolling piston compressor using a multi-objective optimization technique that uses a genetic and evolutionary algorithm. The procedures begin with a pool of compressor designs called population, which were generated pseudo-randomly based on the preset constraints, to arrive at a set of optimum trade-off solutions from the various multiple objective function sets. The optimum solution set allow designers to choose a particular optimum solution that best suited their needs. The cases under examination attempt to optimize combinations of some nine objective functions: the coefficient of performance, refrigerating capacity, motor input power, friction power, indicated work, discharge valve loss, suction valve loss, compressor overall size, and machine cost. There are 18 compressor design variables that are allowed to vary during the optimization process bounded by 23 preset constraints. Results show an effective employment of the multi-objective optimization technique in compressor design.

Reliability-Based Multi-Objective Optimization Methodology for Engineering Systems

2006 ◽  
Author(s):  
Kaushik Sinha
Keyword(s):  
Design Optimization ◽  
Optimization Method ◽  
Performance Measure ◽  
Pareto Optimal ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Automotive Body ◽  
Reliability Based Design ◽  
Pareto Optimal Set ◽  
Optimization Methodology

This paper presents a methodology for reliability-based multi-objective design optimization (RBMODO) of automotive body components under impact scenario. Conflicting design requirements arise as one tries, for example, to minimize structural mass while maximizing energy absorption of an automotive rail section under structural and occupant safety related performance measure constraints. Because deterministic optimum designs obtained without taking uncertainty into account could lead to unreliable designs, a reliability-based approach to design optimization is preferable using a Reliability-based design optimization method. Uncertainty quantification is performed using two methods: reliability based approach and robustness based approach. The technique employed here treats multiple objective functions separately without combining them in any form. A decision-making criterion is subsequently invoked to select the “best” subset of solutions from the obtained non-dominated Pareto optimal solutions. The pareto optimal set obtained in case are compared and contrasted and observations made comparing reliability based approach vis-a`-vis robustness based approach. Deterministic, reliability-based and robustness based multi-objective optimization solutions are compared.

Integrated Design and Multi-Objective Optimization of a Single Stage Heat-Pump Turbocompressor

2013 ◽  
Author(s):  
J. Schiffmann
Keyword(s):  
Design Optimization ◽  
High Efficiency ◽  
Integrated Design ◽  
Heat Pumps ◽  
Small Scale ◽  
Multi Objective Optimization ◽  
Design Constraints ◽  
Multi Objective ◽  
Wide Range ◽  
Standard Design

Small scale turbomachines in domestic heat pumps reach high efficiency and provide oil-free solutions which improve heat-exchanger performance and offer major advantages in the design of advanced thermodynamic cycles. An appropriate turbocompressor for domestic air based heat pumps requires the ability to operate on a wide range of inlet pressure, pressure ratios and mass flows, confronting the designer with the necessity to compromise between range and efficiency. Further the design of small-scale direct driven turbomachines is a complex and interdisciplinary task. Textbook design procedures propose to split such systems into subcomponents and to design and optimize each element individually. This common procedure, however, tends to neglect the interactions between the different components leading to suboptimal solutions. The authors propose an approach based on the integrated philosophy for designing and optimizing gas bearing supported, direct driven turbocompressors for applications with challenging requirements with regards to operation range and efficiency. Using previously validated reduced order models for the different components an integrated model of the compressor is implemented and the optimum system found via multi-objective optimization. It is shown that compared to standard design procedure the integrated approach yields an increase of the seasonal compressor efficiency of more than 12 points. Further a design optimization based sensitivity analysis allows to investigate the influence of design constraints determined prior to optimization such as impeller surface roughness, rotor material and impeller force. A relaxation of these constrains yields additional room for improvement. Reduced impeller force improves efficiency due to a smaller thrust bearing mainly, whereas a lighter rotor material improves rotordynamic performance. A hydraulically smoother impeller surface improves the overall efficiency considerably by reducing aerodynamic losses. A combination of the relaxation of the 3 design constraints yields an additional improvement of 6 points compared to the original optimization process. The integrated design and optimization procedure implemented in the case of a complex design problem thus clearly shows its advantages compared to traditional design methods by allowing a truly exhaustive search for optimum solutions throughout the complete design space. It can be used for both design optimization and for design analysis.

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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