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Hybrid genetic simulated annealing algorithm for agile Earth observation satellite scheduling considering cloud cover distribution 认领 引用
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作者 SUN Haiquan WANG Zhilong +1 位作者 HU Xiaoxuan XIA Wei 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2025年第6期1595-1612,共18页
Agile earth observation satellites(AEOSs)represent a new generation of satellites with three degrees of freedom(pitch,roll,and yaw);they possess a long visible time window(VTW)for ground targets and support imaging at... Agile earth observation satellites(AEOSs)represent a new generation of satellites with three degrees of freedom(pitch,roll,and yaw);they possess a long visible time window(VTW)for ground targets and support imaging at any moment within the VTW.However,different observation times demonstrate different cloud cover distributions,which exhibit different effects on the AEOS observation.Previous studies ignored pitch angles,discretized VTWs,or fixed cloud cover for every VTW,which led to the loss of intermediate observation states,thus these studies are not suitable for AEOS scheduling considering cloud cover distribution.In this study,a relationship formula between the cloud cover and observation time is proposed to calculate the cloud cover for every observation time,and a relationship formula between the observation time and pitch angle is designed to calculate the pitch angle for every observation time in the VTW.A refined model including the pitch angle,roll angle,and cloud cover distribution is established,which can make the scheme closer to the actual application of AEOSs.A hybrid genetic simulated annealing(HGSA)algorithm for AEOS scheduling is proposed,which integrates the advantages of genetic and simulated annealing algorithms and can effectively avoid falling into a local optimal solution.The experiments are conducted to compare the proposed algorithm with the traditional algorithms,the results verify that the proposed model and algorithm are efficient and effective for AEOS scheduling considering cloud cover distribution. 展开更多
关键词 agile Earth observation satellite cloud cover distribution hybrid genetic simulated annealing algorithm
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Hybrid genetic algorithm for parametric optimization of surface pipeline networks in underground natural gas storage harmonized injection and production conditions 认领 引用
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作者 Jun Zhou Zichen Li +4 位作者 Shitao Liu Chengyu Li Yunxiang Zhao Zonghang Zhou Guangchuan Liang 《Natural Gas Industry B》 2025年第2期234-250,共17页
The surface injection and production system(SIPS)is a critical component for effective injection and production processes in underground natural gas storage.As a vital channel,the rational design of the surface inject... The surface injection and production system(SIPS)is a critical component for effective injection and production processes in underground natural gas storage.As a vital channel,the rational design of the surface injection and production(SIP)pipeline significantly impacts efficiency.This paper focuses on the SIP pipeline and aims to minimize the investment costs of surface projects.An optimization model under harmonized injection and production conditions was constructed to transform the optimization problem of the SIP pipeline design parameters into a detailed analysis of the injection condition model and the production condition model.This paper proposes a hybrid genetic algorithm generalized reduced gradient(HGA-GRG)method,and compares it with the traditional genetic algorithm(GA)in a practical case study.The HGA-GRG demonstrated significant advantages in optimization outcomes,reducing the initial cost by 345.371×104 CNY compared to the GA,validating the effectiveness of the model.By adjusting algorithm parameters,the optimal iterative results of the HGA-GRG were obtained,providing new research insights for the optimal design of a SIPS. 展开更多
关键词 Underground natural gas storage Surface injection and production pipeline Parameter optimization Hybrid genetic algorithm
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APPLICATION OF HYBRID GENETIC ALGORITHM IN AEROELASTIC MULTIDISCIPLINARY DESIGN OPTIMIZATION OF LARGE AIRCRAFT 认领 引用 被引量：2
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作者 唐长红 万志强 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2013年第2期109-117,共9页
The genetic/gradient-based hybrid algorithm is introduced and used in the design studies of aeroelastic optimization of large aircraft wings to attain skin distribution,stiffness distribution and design sensitivity.Th... The genetic/gradient-based hybrid algorithm is introduced and used in the design studies of aeroelastic optimization of large aircraft wings to attain skin distribution,stiffness distribution and design sensitivity.The program of genetic algorithm is developed by the authors while the gradient-based algorithm borrows from the modified method for feasible direction in MSC/NASTRAN software.In the hybrid algorithm,the genetic algorithm is used to perform global search to avoid to fall into local optima,and then the excellent individuals of every generation optimized by the genetic algorithm are further fine-tuned by the modified method for feasible direction to attain the local optima and hence to get global optima.Moreover,the application effects of hybrid genetic algorithm in aeroelastic multidisciplinary design optimization of large aircraft wing are discussed,which satisfy multiple constraints of strength,displacement,aileron efficiency,and flutter speed.The application results show that the genetic/gradient-based hybrid algorithm is available for aeroelastic optimization of large aircraft wings in initial design phase as well as detailed design phase,and the optimization results are very consistent.Therefore,the design modifications can be decreased using the genetic/gradient-based hybrid algorithm. 展开更多
关键词 aeroelasticity multidisciplinary design optimization genetic/gradient-based hybrid algorithm large aircraft
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Series-parallel Hybrid Vehicle Control Strategy Design and Optimization Using Real-valued Genetic Algorithm 认领 引用 被引量：16
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作者 XIONG Weiwei YIN Chengliang +1 位作者 ZHANG Yong ZHANG Jianlong 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS 2009年第6期862-868,共7页
Despite the series-parallel hybrid electric vehicle inherits the performance advantages from both series and parallel hybrid electric vehicle,few researches about the series-parallel hybrid electric vehicle have been ... Despite the series-parallel hybrid electric vehicle inherits the performance advantages from both series and parallel hybrid electric vehicle,few researches about the series-parallel hybrid electric vehicle have been revealed because of its complex co nstruction and control strategy.In this paper,a series-parallel hybrid electric bus as well as its control strategy is revealed,and a control parameter optimization approach using the real-valued genetic algorithm is proposed.The optimization objective is to minimize the fuel consumption while sustain the battery state of charge,a tangent penalty function of state of charge(SOC)is embodied in the objective function to recast this multi-objective nonlinear optimization problem as a single linear optimization problem.For this strategy,the vehicle operating mode is switched based on the vehicle speed,and an"optimal line"typed strategy is designed for the parallel control.The optimization parameters include the speed threshold for mode switching,the highest state of charge allowed,the lowest state of charge allowed and the scale factor of the engine optimal torque to the engine maximum torque at a rotational speed.They are optimized through numerical experiments based on real-value genes,arithmetic crossover and mutation operators.The hybrid bus has been evaluated at the Chinese Transit Bus City Driving Cycle via road test,in which a control area network-based monitor system was used to trace the driving schedule.The test result shows that this approach is feasible for the control parameter optimization.This approach can be applied to not only the novel construction presented in this paper,but also other types of hybrid electric vehicles. 展开更多
关键词 series-parallel hybrid electric vehicle control strategy design optimization real-valued genetic algorithm
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Nonlinear amplitude inversion using a hybrid quantum genetic algorithm and the exact zoeppritz equation 认领 引用 被引量：10
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作者 Ji-Wei Cheng Feng Zhang Xiang-Yang Li 《Petroleum Science》 SCIE CAS CSCD 2022年第3期1048-1064,共17页
The amplitude versus offset/angle(AVO/AVA)inversion which recovers elastic properties of subsurface media is an essential tool in oil and gas exploration.In general,the exact Zoeppritz equation has a relatively high a... The amplitude versus offset/angle(AVO/AVA)inversion which recovers elastic properties of subsurface media is an essential tool in oil and gas exploration.In general,the exact Zoeppritz equation has a relatively high accuracy in modelling the reflection coefficients.However,amplitude inversion based on it is highly nonlinear,thus,requires nonlinear inversion techniques like the genetic algorithm(GA)which has been widely applied in seismology.The quantum genetic algorithm(QGA)is a variant of the GA that enjoys the advantages of quantum computing,such as qubits and superposition of states.It,however,suffers from limitations in the areas of convergence rate and escaping local minima.To address these shortcomings,in this study,we propose a hybrid quantum genetic algorithm(HQGA)that combines a self-adaptive rotating strategy,and operations of quantum mutation and catastrophe.While the selfadaptive rotating strategy improves the flexibility and efficiency of a quantum rotating gate,the operations of quantum mutation and catastrophe enhance the local and global search abilities,respectively.Using the exact Zoeppritz equation,the HQGA was applied to both synthetic and field seismic data inversion and the results were compared to those of the GA and QGA.A number of the synthetic tests show that the HQGA requires fewer searches to converge to the global solution and the inversion results have generally higher accuracy.The application to field data reveals a good agreement between the inverted parameters and real logs. 展开更多
关键词 Nonlinear inversion AVO/AVA inversion Hybrid quantum genetic algorithm(HQGA)
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Improved NSGA-ⅡMulti-objective Genetic Algorithm Based on Hybridization-encouraged Mechanism 认领 引用 被引量：10
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作者 Sun Yijie Shen Gongzhang 《Chinese Journal of Aeronautics》 SCIE EI CAS 2008年第6期540-549,共10页
To improve performances of multi-objective optimization algorithms,such as convergence and diversity,a hybridization-encouraged mechanism is proposed and realized in elitist nondominated sorting genetic algorithm(NSGA... To improve performances of multi-objective optimization algorithms,such as convergence and diversity,a hybridization-encouraged mechanism is proposed and realized in elitist nondominated sorting genetic algorithm(NSGA-Ⅱ).This mechanism uses the normalized distance to evaluate the difference among genes in a population.Three possible modes of crossover operators--"Max Distance","Min-Max Distance",and"Neighboring-Max"--are suggested and analyzed.The mode of"Neighboring-Max",which not only takes advantage of hybridization but also improves the distribution of the population near Pareto optimal front,is chosen and used in NSGA-Ⅱon the basis of hybridization-encouraged mechanism(short for HEM-based NSGA-Ⅱ).To prove the HEM-based algorithm,several problems are studied by using standard NSGA-Ⅱand the presented method.Different evaluation criteria are also used to judge these algorithms in terms of distribution of solutions,convergence,diversity,and quality of solutions.The numerical results indicate that the application of hybridization-encouraged mechanism could effectively improve the performances of genetic algorithm.Finally,as an example in engineering practices,the presented method is used to design a longitudinal flight control system,which demonstrates the obtainability of a reasonable and correct Pareto front. 展开更多
关键词 multi-objective optimization genetic algorithms diversity hybridization crossover
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Optimal Adaptive Genetic Algorithm Based Hybrid Signcryption Algorithm for Information Security 认领 引用 被引量：1
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作者 R.Sujatha M.Ramakrishnan +1 位作者 N.Duraipandian B.Ramakrishnan 《Computer Modeling in Engineering & Sciences》 SCIE EI 2015年第5期47-68,共22页
The functions of digital signature and public key encryption are simultaneously fulfilled by signcryption,which is a cryptographic primitive.To securely communicate very large messages,the cryptographic primitive call... The functions of digital signature and public key encryption are simultaneously fulfilled by signcryption,which is a cryptographic primitive.To securely communicate very large messages,the cryptographic primitive called signcryption efficiently implements the same and while most of the public key based systems are suitable for small messages,hybrid encryption(KEM-DEM)provides a competent and practical way.In this paper,we develop a hybrid signcryption technique.The hybrid signcryption is based on the KEM and DEM technique.The KEM algorithm utilizes the KDF technique to encapsulate the symmetric key.The DEM algorithm utilizes the Adaptive Genetic Algorithm based Elliptic curve cryptography algorithm to encrypt the original message.Here,for the security purpose,we introduce the three games and we proved the attackers fail to find the security attributes of our proposed signcryption algorithm.The proposed algorithm is analyzed with Daniel of Service(DOS),Brute Force attack and Man In Middle(MIM)attacks to ensure the secure data transaction. 展开更多
关键词 Hybrid Signcryption KEM DEM Adaptive Genetic Algorithm EllipticCurve Cryptography
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Identification of vibration loads on hydro generator by using hybrid genetic algorithm 认领 引用 被引量：6
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作者 Shouju Li Yingxi Liu 《Acta Mechanica Sinica》 SCIE EI CAS 2006年第6期603-610,共8页
Vibration dynamic characteristics have been a major issue in the modeling and mechanical analysis of large hydro generators. An algorithm is developed for identifying vibration dynamic characteristics by means of hybr... Vibration dynamic characteristics have been a major issue in the modeling and mechanical analysis of large hydro generators. An algorithm is developed for identifying vibration dynamic characteristics by means of hybrid genetic algorithm. From the measured dynamic responses of a hydro generator, an appropriate estimation algorithm is needed to identify the loading parameters, including the main frequencies and amplitudes of vibrating forces. In order to identify parameters in an efficient and robust manner, an optimization method is proposed that combines genetic algorithm with simulated annealing and elitist strategy. The hybrid genetic algorithm is then used to tackle an ill-posed problem of parameter identification, in which the effectiveness of the proposed optimization method is confirmed by its comparison with actual observation data. 展开更多
关键词 Hybrid genetic algorithm Parameteridentification Vibration responses Fieldmeasurement Simulated annealing
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Research of Order Allocation Model Based on Cloud and Hybrid Genetic Algorithm Under Ecommerce Environment 认领 引用 被引量：1
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作者 HUANG Qiang LOU Xin-yuan +1 位作者 WANe Wei NI Shao-quan 《Journal of Shanghai Jiaotong university(Science)》 EI 2013年第3期334-342,共9页
For massive order allocation problem of the third party logistics （TPL） in ecommerce, this paper proposes a general order allocation model based on cloud architecture and hybrid genetic algorithm （GA）, implementin... For massive order allocation problem of the third party logistics （TPL） in ecommerce, this paper proposes a general order allocation model based on cloud architecture and hybrid genetic algorithm （GA）, implementing cloud deployable MapReduce （MR） code to parallelize allocation process, using heuristic rule to fix illegal chromosome during encoding process and adopting mixed integer programming （MIP） as fitness flmction to guarantee rationality of chromosome fitness. The simulation experiment shows that in mass processing of orders, the model performance in a multi-server cluster environment is remarkable superior to that in stand-alone environment. This model can be directly applied to cloud based logistics information platform （LIP） in near future, implementing fast auto-allocation for massive concurrent orders, with great application value. 展开更多
关键词 order allocation cloud architecture hybrid genetic algorithm （GA） MapReduce （MR）
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Groundwater level prediction based on hybrid hierarchy genetic algorithm and RBF neural network 认领 引用 被引量：1
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作者 屈吉鸿 黄强 +1 位作者 陈南祥 徐建新 《Journal of Coal Science & Engineering(China)》 2007年第2期170-174,共5页
As the traditional non-linear systems generally based on gradient descent optimization method have some shortage in the field of groundwater level prediction, the paper, according to structure, algorithm and shortcomi... As the traditional non-linear systems generally based on gradient descent optimization method have some shortage in the field of groundwater level prediction, the paper, according to structure, algorithm and shortcoming of the conventional radial basis function neural network （RBF NN）, presented a new improved genetic algorithm （GA）： hybrid hierarchy genetic algorithm （HHGA）. In training RBF NN, the algorithm can automatically determine the structure and parameters of RBF based on the given sample data. Compared with the traditional groundwater level prediction model based on back propagation （BP） or RBF NN, the new prediction model based on HHGA and RBF NN can greatly increase the convergence speed and precision. 展开更多
关键词 hybrid hierarchy genetic algorithm radial basis function neural network groundwater level prediction model
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Design of Optimal Weight for a Gear Transmission System Using Hybrid Taguchi-Genetic Algorithm 认领 引用 被引量：5
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作者 CHEN Jie WU Shijing HSIEH Chenhuei 《Wuhan University Journal of Natural Sciences》 CAS 2012年第4期331-336,共6页
The gear transmission system has been widely applied in mechanical systems,and many high-performance applications of these systems require low weight.With the aid of establishing the optimization model of the gear tra... The gear transmission system has been widely applied in mechanical systems,and many high-performance applications of these systems require low weight.With the aid of establishing the optimization model of the gear transmission system that consists of an objective function and some constraints(for example,the bending stress,the contact stress,the torsional strength,etc.),the optimal weight design of the gear transmission system can be transformed into the optimization problem for the objective function under the constraints.Moreover,both the shaft and the gear of the gear transmission system are considered simultaneously in our design.The hybrid Taguchi-genetic algorithm(HTGA)is employed to find the optimal design variables and the optimal weight of the system.An illustrated example for the single spur gear reducer is given to show that the optimal weight design problem can be successfully solved using the proposed design scheme.It also proves the high efficiency and feasibility of the algorithm in the gear design. 展开更多
关键词 hybrid Taguchi-genetic algorithm(HTGA) optimal design gear transmission systems optimal weight design
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Solving Travelling Salesman Problem with an Improved Hybrid Genetic Algorithm 认领 引用 被引量：7
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作者 Bao Lin Xiaoyan Sun Sana Salous 《Journal of Computer and Communications》 2016年第15期98-106,共9页
We present an improved hybrid genetic algorithm to solve the two-dimensional Eucli-dean traveling salesman problem (TSP), in which the crossover operator is enhanced with a local search. The proposed algorithm is expe... We present an improved hybrid genetic algorithm to solve the two-dimensional Eucli-dean traveling salesman problem (TSP), in which the crossover operator is enhanced with a local search. The proposed algorithm is expected to obtain higher quality solutions within a reasonable computational time for TSP by perfectly integrating GA and the local search. The elitist choice strategy, the local search crossover operator and the double-bridge random mutation are highlighted, to enhance the convergence and the possibility of escaping from the local optima. The experimental results illustrate that the novel hybrid genetic algorithm outperforms other genetic algorithms by providing higher accuracy and satisfactory efficiency in real optimization processing. 展开更多
关键词 Genetic Algorithm Hybrid Local Search TSP
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The RHSA Strategy for the Allocation of Outbound Containers Based on the Hybrid Genetic Algorithm 认领 引用 被引量：2
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作者 Meilong Le Hang Yu 《Journal of Marine Science and Application》 2013年第3期344-350,共7页
Secure storage yard is one of the optimal core goals of container transportation;thus,making the necessary storage arrangements has become the most crucial part of the container terminal management systems(CTMS).This ... Secure storage yard is one of the optimal core goals of container transportation;thus,making the necessary storage arrangements has become the most crucial part of the container terminal management systems(CTMS).This paper investigates a random hybrid stacking algorithm(RHSA)for outbound containers that randomly enter the yard.In the first stage of RHSA,the distribution among blocks was analyzed with respect to the utilization ratio.In the second stage,the optimization of bay configuration was carried out by using the hybrid genetic algorithm.Moreover,an experiment was performed to test the RHSA.The results show that the explored algorithm is useful to increase the efficiency. 展开更多
关键词 random hybrid stacking algorithm genetic algorithm container yard operation container stowage plan handling cost utilization ratio
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Multi-Period Model of Portfolio Investment and Adjustment Based on Hybrid Genetic Algorithm 认领 引用
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作者 荣喜民 卢美萍 邓林 《Transactions of Tianjin University》 EI CAS 2009年第6期415-422,共8页
This paper proposes a multi-period portfolio investment model with class constraints, transaction cost, and indivisible securities. When an investor joins the securities market for the first time, he should decide on ... This paper proposes a multi-period portfolio investment model with class constraints, transaction cost, and indivisible securities. When an investor joins the securities market for the first time, he should decide on portfolio investment based on the practical conditions of securities market. In addition, investors should adjust the portfolio according to market changes, changing or not changing the category of risky securities. Markowitz meanvariance approach is applied to the multi-period portfolio selection problems. Because the sub-models are optimal mixed integer program, whose objective function is not unimodal and feasible set is with a particular structure, traditional optimization method usually fails to find a globally optimal solution. So this paper employs the hybrid genetic algorithm to solve the problem. Investment policies that accord with finance market and are easy to operate for investors are put forward with an illustration of application. 展开更多
关键词 portfolio transaction cost class constraint hybrid genetic algorithm
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Multicast Routing Based on Hybrid Genetic Algorithm 认领 引用
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作者 CAO Yuan-da CAI Gui 《Journal of Beijing Institute of Technology》 EI CAS 2005年第2期130-134,共5页
A new multicast routing algorithm based on the hybrid genetic algorithm(HGA)is proposed.The coding pattern based on the number of routing paths is used.A fitness function that is computed easily and makes algorithm qu... A new multicast routing algorithm based on the hybrid genetic algorithm(HGA)is proposed.The coding pattern based on the number of routing paths is used.A fitness function that is computed easily and makes algorithm quickly convergent is proposed.A new approach that defines the HGA's parameters is provided.The simulation shows that the approach can increase largely the convergent ratio,and the fitting values of the parameters of this algorithm are different from that of the original algorithms.The optimal mutation probability of HGA equals 0.50 in HGA in the experiment,but that equals 0.07 in SGA.It has been concluded that the population size has a significant influence on the HGA's convergent ratio when it's mutation probability is bigger.The algorithm with a small population size has a high average convergent rate.The population size has little influence on HGA with the lower mutation probability. 展开更多
关键词 multicast routing hybrid genetic algorithm(HGA) simulation algorithm Steiner tree
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Two-Dimensional Nesting System Based on Hybrid Genetic Algorithm 认领 引用
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作者 WU Qingming YANG Wei ZHANG Qiang ZHOU Junjie 《Wuhan University Journal of Natural Sciences》 CAS 2009年第1期60-64,共5页
According to the cutting stock problem of 2-dimensional shapes, a nesting system （NS） based on hybrid genetic algorithm （HGA） is established. The system optimizes the sequence and angles of polygons with hybrid Ge... According to the cutting stock problem of 2-dimensional shapes, a nesting system （NS） based on hybrid genetic algorithm （HGA） is established. The system optimizes the sequence and angles of polygons with hybrid Genetic Algorithm to accomplish the superior solution. It nests the irregular shape directly without covering irregular shapes with a rectangle. It also improves the decoding strategy of 2-dimensional shapes nesting based on the classical bottom-left strategy, makes the new strategy be universal to convex polygons, concave polygons and line-circular composted polygons. 展开更多
关键词 nesting system hybrid genetic algorithm （HGA） regular and circular polygon bottom-left strategy
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A hybrid genetic algorithm for the electric vehicle routing problem with time windows 认领 引用 被引量：3
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作者 Qixing Liu Peng Xu +1 位作者 Yuhu Wu Tielong Shen 《Control Theory and Technology》 EI CSCD 2022年第2期279-286,共8页
Driven by the new legislation on greenhouse gas emissions,carriers began to use electric vehicles(EVs)for logistics transportation.This paper addresses an electric vehicle routing problem with time windows(EVRPTW).The... Driven by the new legislation on greenhouse gas emissions,carriers began to use electric vehicles(EVs)for logistics transportation.This paper addresses an electric vehicle routing problem with time windows(EVRPTW).The electricity consumption of EVs is expressed by the battery state-of-charge(SoC).To make it more realistic,we take into account the terrain grades of roads,which affect the travel process of EVs.Within our work,the battery SoC dynamics of EVs are used to describe this situation.We aim to minimize the total electricity consumption while serving a set of customers.To tackle this problem,we formulate the problem as a mixed integer programming model.Furthermore,we develop a hybrid genetic algorithm(GA)that combines the 2-opt algorithm with GA.In simulation results,by the comparison of the simulated annealing(SA)algorithm and GA,the proposed approach indicates that it can provide better solutions in a short time. 展开更多
关键词 Electric vehicles Vehicle routing Battery SoC Hybrid genetic algorithm
Optimization of the seismic processing phase-shift plus finite-difference migration operator based on a hybrid genetic and simulated annealing algorithm 认领 引用 被引量：2
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作者 Luo Renze Huang Yuanyi +2 位作者 Liang Xianghao Luo Jun Cao Ying 《Petroleum Science》 SCIE CAS CSCD 2013年第2期190-194,共5页
Although the phase-shift seismic processing method has characteristics of high accuracy, good stability, high efficiency, and high-dip imaging, it is not able to adapt to strong lateral velocity variation. To overcome... Although the phase-shift seismic processing method has characteristics of high accuracy, good stability, high efficiency, and high-dip imaging, it is not able to adapt to strong lateral velocity variation. To overcome this defect, a finite-difference method in the frequency-space domain is introduced in the migration process, because it can adapt to strong lateral velocity variation and the coefficient is optimized by a hybrid genetic and simulated annealing algorithm. The two measures improve the precision of the approximation dispersion equation. Thus, the imaging effect is improved for areas of high-dip structure and strong lateral velocity variation. The migration imaging of a 2-D SEG/EAGE salt dome model proves that a better imaging effect in these areas is achieved by optimized phase-shift migration operator plus a finite-difference method based on a hybrid genetic and simulated annealing algorithm. The method proposed in this paper is better than conventional methods in imaging of areas of high-dip angle and strong lateral velocity variation. 展开更多
关键词 Migration operator phase-shift plus finite-difference hybrid algorithm genetic andsimulated annealing algorithm optimization coefficient
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Optimization of Multi-Execution Modes and Multi-Resource-Constrained Offshore Equipment Project Scheduling Based on a Hybrid Genetic Algorithm 认领 引用 被引量：1
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作者 Qi Zhou Jinghua Li +2 位作者 Ruipu Dong Qinghua Zhou Boxin Yang 《Computer Modeling in Engineering & Sciences》 SCIE EI 2023年第2期1263-1281,共19页
Offshore engineering construction projects are large and complex,having the characteristics of multiple execution modes andmultiple resource constraints.Their complex internal scheduling processes can be regarded as r... Offshore engineering construction projects are large and complex,having the characteristics of multiple execution modes andmultiple resource constraints.Their complex internal scheduling processes can be regarded as resourceconstrained project scheduling problems(RCPSPs).To solve RCPSP problems in offshore engineering construction more rapidly,a hybrid genetic algorithmwas established.To solve the defects of genetic algorithms,which easily fall into the local optimal solution,a local search operation was added to a genetic algorithm to defend the offspring after crossover/mutation.Then,an elitist strategy and adaptive operators were adopted to protect the generated optimal solutions,reduce the computation time and avoid premature convergence.A calibrated function method was used to cater to the roulette rules,and appropriate rules for encoding,decoding and crossover/mutation were designed.Finally,a simple network was designed and validated using the case study of a real offshore project.The performance of the genetic algorithmand a simulated annealing algorithmwas compared to validate the feasibility and effectiveness of the approach. 展开更多
关键词 Offshore project multi-execution modes resource-constrained project scheduling hybrid genetic algorithm
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Identification of Magnetic Bearing Stiffness and Damping Based on Hybrid Genetic Algorithm 认领 引用 被引量：1
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作者 Zhao Chen Zhou Jin +2 位作者 Xu Yuanping Di Long Ji Minlai 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2017年第2期211-219,共9页
Identifying the stiffness and damping of active magnetic bearings(AMBs)is necessary since those parameters can affect the stability and performance of the high-speed rotor AMBs system.A new identification method is pr... Identifying the stiffness and damping of active magnetic bearings(AMBs)is necessary since those parameters can affect the stability and performance of the high-speed rotor AMBs system.A new identification method is proposed to identify the stiffness and damping coefficients of a rotor AMB system.This method combines the global optimization capability of the genetic algorithm(GA)and the local search ability of Nelder-Mead simplex method.The supporting parameters are obtained using the hybrid GA based on the experimental unbalance response calculated through the transfer matrix method.To verify the identified results,the experimental stiffness and damping coefficients are employed to simulate the unbalance responses for the rotor AMBs system using the finite element method.The close agreement between the simulation and experimental data indicates that the proposed identified algorithm can effectively identify the AMBs supporting parameters. 展开更多
关键词 magnetic bearing hybrid genetic algorithm bearing parameters finite element model
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