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Using genetic/simulated annealing algorithm to solve disassembly sequence planning

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Journal of Systems Engineering and Electronics 2009年第4期20卷 906-912页

作者： Wu Hao Zuo Hongfu Coll. of Civil Aviation Nanjing Univ. of Aeronautics and Astronautics Nanjing 210016 P. R. China

Disassembly sequence planning （DSP） plays a significant role in maintenance planning of the aircraft. It is used during the design stage for the analysis of maintainability of the aircraft. To solve product disassembly sequence planning problems efficiently, a product disassembly hybrid graph model, which describes the connection, non-connection and precedence relationships between the product parts, is established based on the characteristic of disassembly. Farther, the optimization model is provided to optimize disassembly sequence. And the solution methodology based on the genetic/simulated annealing algorithm with binaxy-tree algorithm is given. Finally, an example is analyzed in detail, and the result shows that the model is correct and efficient.

关键词： disassembly sequence planning disassembly hybrid graph connection matrix precedence matrix binary-tree algorithms simulated annealing algorithm genetic algorithm.

Structural optimization and segregation behavior of quaternary alloy nanoparticles based on simulated annealing algorithm

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Chinese Physics B 2016年第5期25卷 151-158页

作者：陆欣泽邵桂芳许两有刘暾东文玉华 Department of Physics Xiamen University Department of Automation Xiamen University

Alloy nanoparticles exhibit higher catalytic activity than monometallic nanoparticles, and their stable structures are of importance to their applications. We employ the simulated annealing algorithm to systematically explore the stable structure and segregation behavior of tetrahexahedral Pt–Pd–Cu–Au quaternary alloy nanoparticles. Three alloy nanoparticles consisting of 443 atoms, 1417 atoms, and 3285 atoms are considered and compared. The preferred positions of atoms in the nanoparticles are analyzed. The simulation results reveal that Cu and Au atoms tend to occupy the surface, Pt atoms preferentially occupy the middle layers, and Pd atoms tend to segregate to the inner layers. Furthermore, Au atoms present stronger surface segregation than Cu ones. This study provides a fundamental understanding on the structural features and segregation phenomena of multi-metallic nanoparticles.

关键词： alloy nanoparticle simulated annealing algorithm structural stability segregation

Study on Multi-stream Heat Exchanger Network Synthesis with Parallel Genetic/simulated annealing algorithm

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Chinese Journal of Chemical Engineering 2004年第1期12卷 66-77页

作者：魏关锋姚平经 LUOXing ROETZELWilfried InstituteofProcessSystemsEngineering DalianUniversityofTechnologyDalian116012China InstituteofThermodynamics UniversityoftheFederalArmedForcesHamburgD-22039HamburgGermany

The multi-stream heat exchanger network synthesis (HENS) problem can be formulated as a mixed integer nonlinear programming model according to Yee et al. Its nonconvexity nature leads to existence of more than one optimum and computational difficulty for traditional algorithms to find the global optimum. Compared with deterministic algorithms, evolutionary computation provides a promising approach to tackle this problem. In this paper, a mathematical model of multi-stream heat exchangers network synthesis problem is setup. Different from the assumption of isothermal mixing of stream splits and thus linearity constraints of Yee et al., non-isothermal mixing is supported. As a consequence, nonlinear constraints are resulted and nonconvexity of the objective function is added. To solve the mathematical model, an algorithm named GA/SA (parallel genetic/simulated annealing algorithm) is detailed for application to the multi-stream heat exchanger network synthesis problem. The performance of the proposed approach is demonstrated with three examples and the obtained solutions indicate the presented approach is effective for multi-stream HENS.

关键词： multi-stream heat exchanger network synthesis non-isothermal mixing mixed integer nonlinear programming model genetic algorithm simulated annealing algorithm hybrid algorithm

An Improved Multi-Objective Hybrid Genetic-simulated annealing algorithm for AGV Scheduling under Composite Operation Mode

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Computers, Materials & Continua 2023年第12期77卷 3443-3466页

作者： Jiamin Xiang Ying Zhang Xiaohua Cao Zhigang Zhou School of Transportation and Logistics Engineering Wuhan University of TechnologyWuhan430063China Hubei Plog Technology Co. Ltd.Wuhan430000China

This paper presents an improved hybrid algorithm and a multi-objective model to tackle the scheduling problem of multiple Automated Guided Vehicles(AGVs)under the composite operation *** multi-objective model aims to minimize the maximum completion time,the total distance covered by AGVs,and the distance traveled while *** improved hybrid algorithm combines the improved genetic algorithm(GA)and the simulated annealing algorithm(SA)to strengthen the local search ability of the algorithm and improve the stability of the calculation *** on the characteristics of the composite operation mode,the authors introduce the combined coding and parallel decoding mode and calculate the fitness function with the grey entropy parallel analysis method to solve the multi-objective *** grey entropy parallel analysis method is a combination of the grey correlation analysis method and the entropy weighting method to solve multi-objective solving problems.A task advance evaluation strategy is proposed in the process of crossover and mutation operator to guide the direction of crossover and *** computational experiments results show that the improved hybrid algorithm is better than the GA and the genetic algorithm with task advance evaluation strategy(AEGA)in terms of convergence speed and solution results,and the effectiveness of the multi-objective solution is *** three objectives are optimized and the proposed algorithm has an optimization of 7.6%respectively compared with the GA and 3.4%compared with the AEGA in terms of the objective of maximum completion time.

关键词： AGV scheduling composite operation mode genetic algorithm simulated annealing algorithm task advance evaluation strategy

Magnetic Coupler Robust Optimization Design for Electric Vehicle Wireless Charger Based on Improved simulated annealing algorithm

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Automotive Innovation 2022年第1期5卷 29-42页

作者： Zhenpo Wang Lantian Li Junjun Deng Baokun Zhang Shuo Wang School of Mechanical Engineering Beijing Institute of TechnologyNO.5 Zhongguancun StreetBeijingChina Collaborative Innovation Center of Electric Vehicles in Beijing NO.5 Zhongguancun StreetBeijingChina

Fleets of autonomous vehicles including shuttle buses,freight trucks,and road sweepers will be deployed in the Olympic Vil-lage during Beijing 2022 Winter *** requires intelligent charging infrastructure based on wireless power transfer technology to be *** increase the misalignment tolerance of a high-power wireless charger,the robustness of the magnetic coupler should be *** paper presents a new type of unipolar coupler,which is composed of three con-nected coils in *** dimensional configuration of the coils is analyzed by the finite element *** characteristic parameters of the coil are identified with their influence on the self-inductance and coupling *** expert model is built,whose feasibility can be verified in the aimed design *** with the expert model,an improved simulated annealing algorithm with a backtracking mechanism is *** primary coil can reach the expected characteristics from any starting parameter combination through the proposed optimization *** the same conditions in terms of external circuit parameters,ferrite usage,and aluminum shielding,the offset sensitivity of the magnetic coupler can be reduced from 58.79%to 18.89%.A prototype is established,validating the feasibility of the proposed coil structure with the optimized parameter algorithm.

关键词： Wireless power transfer Magnetic coupler simulated annealing algorithm Robust optimization

NEW MULTIOBJECTIVE simulated annealing algorithm AND ITS APPLICATION TO TURBINE CASCADES’ DESIGN

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Chinese Journal of Mechanical Engineering 1999年第1期12卷 51-56页

作者： Tong Tong Feng Zhenping Xi’an Jiaotong University Xi'an Jiaotong Univ Xi'an China

A new kind of multiobjective simulated annealing algorithm is proposed,in which the concept of non dominated character is introduced and a new multiobjective acceptance criterion is set *** optimization example of a typical mathematical problem with two minimum objective functions indicates that all of the solutions contract to the set of the non dominated points,and the variation trend of the optimal solutions is verified to be identical with that obtained using Genetic Algor *** new developed algorithm is then applied to the multiobjective optimization design of turbine cascades,in which it is coupled with the aerodynamics computation of the cascade flow fields and performance and the calculated loss coefficient and work potential of the cascade are considered as the objective functions,thus setting up a technique to the engineering optimization design for the *** optimization results,by the view of a group of optimal solutions,show that the algorithm is superior to the traditional technique of multiobjective optimization design and can be applied to more than two objective optimization cascade design problem or other engineering multiobjective optimization designs.

关键词： simulated annealing algorithm Multiobjective Optimization design Turbine cascade

Multi-Objective Optimization for Structure Crashworthiness Based on Kriging Surrogate Model and simulated annealing algorithm

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Journal of Shanghai Jiaotong university(Science) 2020年第6期25卷 727-738页

作者： SUN Xilong WANG Dengfeng LI Ruheng ZHANG Bin School of Engineering Dali UniversityDali 671003YunnanChina Andi Sales Division FAW-VW Automotive Co.Ltd.Changchun 130011China State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun 130025China Logistics Group Jilin UniversityChangchun 130025China

Multi-objective optimization of crashworthiness in automobile front-end structure was performed,and finite element model(FEM)was validated by experimental results to ensure that FEM can predict the response value with sufficient *** design variables and four crashworthiness indicators were *** orthogonal design method,18 FEMs were established,and the response values of crashworthiness indicators were *** using the variable-response specimen matrix,Kriging surrogate model(KSM)was constructed to replace FEM to refect the function correlation between variables and *** accuracy of KSM was also ***,the simulated annealing optimization algorithm was implemented in KSM to seek optimal and reliable *** on the optimal results and comparison analysis,the 9096-th iteration point was the optimal *** the intrusion of firewall and the mass of optimal structure increased slightly,the vehicle acceleration of the optimal solution decreased by 6.9%,which fectively reduced the risk of occupant injury.

关键词： crashworthiness multi-objective optimization Kriging surrogate model(KSM) simulated annealing algorithm

Usage of simulated annealing algorithm in Design of Optical Thin Film

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Journal of Shanghai Jiaotong university(Science) 2011年第3期16卷 372-374页

作者：王文梁戎晓红 Department of Physics Nanchang University Xuzhou Institute of Industry Technology

simulated annealing algorithm is a mathematic model,which imitates the physical process of annealing. And optical thin film is widely used in many *** design is difficult and can be regarded as an optimization *** this paper,we use the simulated annealing algorithm to design an edge filter,which is composed of 20 dielectric thin film layers with TiO2 and *** simulated annealing algorithm is a very robust algorithm for optical thin film design.

关键词： simulated annealing algorithm optical thin film edge filter

Parametric optimization and performance comparison of organic Rankine cycle with simulated annealing algorithm

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Journal of Central South University 2012年第9期19卷 2584-2590页

作者：王志奇周乃君张家奇郭静王晓元 School of Energy Science and Engineering Central South University Institute of Mechanical Engineering Xiangtan University

Taking the ratio of heat transfer area to net power and heat recovery efficiency into account, a multi-objective mathematical model was developed for organic Rankine cycle （ORC）. Working fluids considered were R123, R134a, R141b, R227ea and R245fa. Under the given conditions, the parameters including evaporating and condensing pressures, working fluid and cooling water velocities were optimized by simulated annealing algorithm. The results show that the optimal evaporating pressure increases with the heat source temperature increasing. Compared with other working fluids, R123 is the best choice for the temperature range of 100--180℃ and R141 b shows better performance when the temperature is higher than 180 ℃. Economic characteristic of system decreases rapidly with the decrease of heat source temperature. ORC system is uneconomical for the heat source temperature lower than 100℃.

关键词： parametric optimization organic Rankine cycle simulated annealing algorithm working fluid low-temperature source