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Efficient Constellation Design Based on Improved non-dominated sorting genetic algorithm-II

JOURNAL OF COMPUTERS 2012年第6期7卷 1337-1344页

作者： Mao, Tengyue Xu, Zhengquan Hou, Rui Wuhan Univ State Key Lab Informat Engn Surveying Mapping & R Wuhan 430079 Hubei Peoples R China South Cent Univ Nationalities Coll Comp Sci Wuhan 430074 Hubei Peoples R China

Constellation design is a typical multiple peaks, multiple valleys and non-linear multi-objective optimization problem. How to design satellite constellation is one of the key sectors of research in the aerospace field. In this paper, in order to improve the global convergence and diversity performance of traditional constellation optimization algorithm, multi-parent arithmetic crossover and SBX crossover operator of NSGA-II are used to improve searching capability of this algorithm. Meanwhile, Gaussian mutation and Cauchy mutation, with diversity of population, make the algorithm get better behaviors in convergence and diversity of finding solutions. Based on the methods, an improvement NSGA-II is presented to design constellation in the paper. The algorithm uses fixed length chromosome representation. Real coding is adopted for that the problem has both integer continuous variables. Combining the coverage assessment criterions, an orbit parameters optimization framework based on nondominated sorting genetic algorithm (NSGA-II) was proposed. This method is applied to a detailed example, and result shows that a group of Pareto solutions with good spread can be achieved, which gives strong support to constellation scheme determination.

关键词： Multi-objective Optimization genetic algorithm non-dominated sorting genetic algorithm Satellite Constellation

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Fuzzy ranking based non-dominated sorting genetic algorithm-II for network overload alleviation

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ARCHIVES OF ELECTRICAL ENGINEERING 2014年第3期63卷 367-384页

作者： Pandiarajan, K. Babulal, C. K. Pandian Saraswathi Yadav Engn Coll Dept Elect & Elect Engn Arasanoor India Thiagarajar Coll Engn Dept Elect & Elect Engn Madurai Tamil Nadu India

This paper presents an effective method of network overload management in power systems. The three competing objectives 1) generation cost 2) transmission line overload and 3) real power loss are optimized to provide pareto-optimal solutions. A fuzzy ranking based non-dominated sorting genetic algorithm-II (NSGA-II) is used to solve this complex nonlinear optimization problem. The minimization of competing objectives is done by generation rescheduling. Fuzzy ranking method is employed to extract the best compromise solution out of the available non-dominated solutions depending upon its highest rank. N-1 contingency analysis is carried out to identify the most severe lines and those lines are selected for outage. The effectiveness of the proposed approach is demonstrated for different contingency cases in IEEE 30 and IEEE 118 bus systems with smooth cost functions and their results are compared with other single objective evolutionary algorithms like Particle swarm optimization (PSO) and Differential evolution (DE). Simulation results show the effectiveness of the proposed approach to generate well distributed pareto-optimal non-dominated solutions of multi-objective problem.

关键词： non-dominated sorting genetic algorithm generation rescheduling particle swarm optimization differential evolution overload index

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Optimization of Pre-Treatment Parameters before Diamond Coating using non-dominated sorting genetic algorithm (NSGA-II)

Optimization of Pre-Treatment Parameters before Diamond Coat...

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2nd International Conference on Advanced Material Research (ICAMR 2012)

作者： Golshan, Abolfazl Shirdar, Mostafa Rezazadeh Gohery, Scott Alvansazyazdi, Mohammadfarid Isfahan Univ Technol Fac Mech Engn Esfahan Iran Univ Teknol Malaysia Fac Mech Engn Skudai 81310 Malaysia Univ Teknol Malaysia Fac Civil Engn Skudai 81310 Malaysia

ISBN: (纸本)9783037853634

In this study a single step of the chemical pre-treatment is implemented to tungsten carbide (WC 6 [%]) at the surface of the substrate in order to solve poor adhesion problem. During the pre-treatment process, numerous parameters such as etching time, acid temperature and concentration affect on the surface roughness and Cobalt content of WC-Co substrate are investigated. Optimal selection of these parameters is one of the significant issues to achieve high-quality work-piece in etching process. Thus, the statistical model based on nonlinear polynomial equations is developed for the different responses. non-dominated sorting genetic algorithm (NSGA-II) with the use of MATLAB Software codes is used to solve multi-objective optimization problem in order to provide a preferred solution for a process engineer in a short period of time.

关键词： pre-treatment process surface roughness cobalt content statistical model multi-objective optimization non-dominated sorting genetic algorithm

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A New Image Watermarking Scheme Using non-dominated sorting genetic algorithm II

A New Image Watermarking Scheme Using Non-dominated Sorting ...

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International Symposium on Biometrics and Security Technologies (ISBAST)

作者： Lee, Jiann-Shu Huang, Fei-Hsiang Kuo, Hsiao-Chen Natl Univ Tainan Dept Comp Sci & Informat Engn Tainan Taiwan Far East Univ Dept Management Informat Syst Tainan Taiwan

ISBN: (纸本)9780769550107

In recent years, singular value decomposition has become a popular tool for image watermarking. In this paper, we propose a new blind watermarking scheme by quantizing the singular values of wavelet component. To optimize the system performance, we treat the image watermarking as a multi-objective optimization problem based on non-dominated sorting genetic algorithm II. Based on this new perspective, the inherent conflict existing in image fidelity and watermark robustness for image watermarking can be objectively handled. The experimental study shows that our method indeed provide superior performance.

关键词： watermarking singular value decomposition non-dominated sorting genetic algorithm

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The optimization methods based on non-dominated sorting genetic algorithm for scheduling of material flow in mineral process

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IMACS Multiconference on Computational Engineering in Systems Applications (CESA 2006)

作者： Ma, E. J. Chai, T. Y. Bai, R. Northeastern Univ Res Ctr Automat Shenyang 110004 Liaoning Peoples R China

ISBN: (纸本)9787302139225

Scheduling of material flow of each section in mineral process affects not only the stability and continuity of mineral process but also realization of global production indices of the process. Synthetically considering such factors as grade of concentrate, output of concentrate, concentration-ratio and capacity of buffer storage, we establish multi-objective programming model based on object of minimized fluctuation of mineral process assembly load and minimized punish fees, and apply improved non-dominated sorting genetic algorithm to solve the model. Consequently, the optimum processing quantity of each section in material process can be obtained, which provide the reference in seeking the reasonable scheduling of material flow in mineral enterprise.

关键词： mineral process scheduling of material flow multi-objective programming non-dominated sorting genetic algorithm

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A Product Configuration Optimization Method Based on non-dominated sorting genetic algorithm

A Product Configuration Optimization Method Based on Non-dom...

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Global Conference on Digital Design and Manufacturing Technology

作者： Sun, W. H. Lu, W. C. Lin, D. Y. China Jiliang Univ Coll Mech & Elect Engn Hangzhou 310027 Zhejiang Peoples R China

ISBN: (纸本)9783037850718

In order to realize the complex product rapid configuration design in the environment of mass configuration (MC), the non-dominated sorting genetic algorithm (NGSA) for product rapid configuration design is proposed in this paper. The model of multi-objective product configuration optimization is established, and hierarchical analysis is made for configuration design. By comparing the similarity and integrity of requirement and instance, the sequence of retrieval instances is given according to the reuse degree, and multi-objective optimization configuration based on NGSA is realized. Finally, the validity and practicability of the method is verified by an instance which is applied in rapid configuration design of the drive module of tuyere puncher.

关键词： Multi-objective optimization Knowledge reuse Product configuration non-dominated sorting genetic algorithm

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Modeling and optimization of cylindrical wire electro discharge machining of AISI D3 tool steel using non-dominated sorting genetic algorithm

Modeling and optimization of cylindrical wire electro discha...

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International Conference on Graphic and Image Processing (ICGIP)

作者： Golshan, Abolfazl Gohery, Scott Ayob, Amran Isfahan Univ Technol Fac Mech Engn Esfahan Iran Univ Teknol Malaysia Fac Mech Engn Skudai Malaysia

ISBN: (纸本)9780819489326

In this study the influence of Cylindrical Wire Electro Discharge Machining on surface roughness and material removal rate is conducted. From experimental DOE method and mathematical modeling, the importance and correlation between corresponding parameters and process output characterization are studied. The investigated input parameters include electrical current, pulse-off time, voltage, rotation speed and cone angle. The non-dominated sorting genetic algorithm is then applied on the outputs to generate appropriate optimized models. The optimization procedure shows that the suggested method results in a high performance problem solving.

关键词： Cylindrical Wire Electro Discharge Machining Surface roughness Material removal rate non-dominated sorting genetic algorithm

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Multi-objective optimal design of magnetorheological engine mount based on an improved non-dominated sorting genetic algorithm

Multi-objective optimal design of magnetorheological engine ...

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Conference on Active and Passive Smart Structures and Integrated Systems

作者： Zheng Ling Duan Xuwei Deng Zhaoxue Li Yinong Chongqing Univ State Key Lab Mech Transmiss Chongqing 400044 Peoples R China

ISBN: (纸本)9780819499837

A novel flow-mode magneto-rheological (MR) engine mount integrated a diaphragm de-coupler and the spoiler plate is designed and developed to isolate engine and the transmission from the chassis in a wide frequency range and overcome the stiffness in high frequency. A lumped parameter model of the MR engine mount in single degree of freedom system is further developed based on bond graph method to predict the performance of the MR engine mount accurately. The optimization mathematical model is established to minimize the total of force transmissibility over several frequency ranges addressed. In this mathematical model, the lumped parameters are considered as design variables. The maximum of force transmissibility and the corresponding frequency in low frequency range as well as individual lumped parameter are limited as constraints. The multiple interval sensitivity analysis method is developed to select the optimized variables and improve the efficiency of optimization process. An improved non-dominated sorting genetic algorithm (NSGA-II) is used to solve the multi-objective optimization problem. The synthesized distance between the individual in Pareto set and the individual in possible set in engineering is defined and calculated. A set of real design parameters is thus obtained by the internal relationship between the optimal lumped parameters and practical design parameters for the MR engine mount. The program flowchart for the improved non-dominated sorting genetic algorithm (NSGA-II) is given. The obtained results demonstrate the effectiveness of the proposed optimization approach in minimizing the total of force transmissibility over several frequency ranges addressed.

关键词： Magneto-rheological mount optimal design lumped parameter model bond graph method multi-objective non-dominated sorting genetic algorithm

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Operative generative design using non-dominated sorting genetic algorithm II (NSGA-II)

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AUTOMATION IN CONSTRUCTION 2023年第1期155卷

作者： Bailey, Elnaz Tafrihi Caldas, Luisa Univ Calif Berkeley Dept Architecture Berkeley CA USA Univ Calif Berkeley XR Lab Berkeley CA USA Lawrence Berkeley Natl Lab Berkeley CA USA Univ Calif Berkeley Coll Environm Design Dept Architecture Berkeley CA 94720 USA

Massing studies during the early stages of architectural design play an essential role in determining the final building's performance across design objectives. This paper aims to answer the question: How can early-stage architectural design workflows be translated into a generative design process to create valuable massing solutions? In response, a new application of the non-dominated sorting genetic algorithm II (NSGA-II) using the Pymoo framework is proposed for the field of Operative Design. Nine experiments are discussed that test the algorithm's geometry optimization capabilities based on objective functions reflecting common architectural design goals, including Floor Area Ratio (FAR), non-Passive Zone (NPZ), Roofs and Best Oriented Surfaces (RBOS), and Usable Open Space (UOS). Selected cases are visualized among non-dominated solutions in each experiment demonstrating the trade-offs between different objectives while programmatically generating successful building designs. In the future, the proposed generative design workflow can be implemented to run optimizations independently from other software within immersive environments.

关键词： Generative design non-dominated sorting genetic algorithm (NSGA-II) Operative design Early-stage architecture design Building massing Building performance rules-of-thumb

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LEO Satellite Downlink Distributed Jamming Optimization Method Using a non-dominated sorting genetic algorithm

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REMOTE SENSING 2024年第6期16卷 1006页

作者： Tang, Chengkai Ding, Jiawei Zhang, Lingling Northwestern Polytech Univ Sch Elect & Informat Xian 710072 Peoples R China Northwestern Polytech Univ Shenzhen Res & Dev Inst Shenzhen 518063 Peoples R China Northwestern Polytech Univ Sch Marine Sci & Technol Xian 710072 Peoples R China

Due to their low orbit, low-Earth-orbit (LEO) satellites possess advantages such as minimal transmission delay, low link loss, flexible deployment, diverse application scenarios, and low manufacturing costs. Moreover, by increasing the number of satellites, the system capacity can be enhanced, making them the core of future communication systems. However, there have been instances where malicious actors used LEO satellite communication equipment to illegally broadcast events in large sports stadiums or engage in unauthorized leakage of military secrets in sensitive military areas. This has become an urgent issue in the field of communication security. To combat and prevent abnormal and illegal communication activities using LEO satellites, this study proposes a LEO satellite downlink distributed jamming optimization method using a non-dominated sorting genetic algorithm. Firstly, a distributed jamming system model for the LEO satellite downlink is established. Then, using a non-dominated sorting genetic algorithm, the jamming parameters are optimized in the power, time, and frequency domains. Field jamming experiments were conducted in the southwest outskirts of Xi'an, China, targeting the LEO constellation of the China Satellite Network. The results indicate that under the condition that the jamming coverage rate is no less than 90%, the proposed method maximizes jamming power, minimizes time delay, and minimizes frequency compensation compared to existing jamming optimization methods, effectively improving the real-time jamming performance and success rate.

关键词： LEO satellite downlink distributed jamming non-dominated sorting genetic algorithm

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