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基于混合遗传算法的压气机叶型自动优化设计 被引量:10
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作者 金东海 展昭 桂幸民 《推进技术》 EI CAS CSCD 北大核心 2006年第4期349-353,共5页
基于实数编码的自适应遗传算法与复合形法相结合,构成了自动优化设计所应用的混合遗传算法。与自适应遗传算法相比,混合遗传算法的局部搜索能力得到增强,运行效率有明显提高。压气机叶型定义采用的是Bezier函数参数化定义方法。该方法... 基于实数编码的自适应遗传算法与复合形法相结合,构成了自动优化设计所应用的混合遗传算法。与自适应遗传算法相比,混合遗传算法的局部搜索能力得到增强,运行效率有明显提高。压气机叶型定义采用的是Bezier函数参数化定义方法。该方法可以较好的拟合叶型曲线,并通过较少控制点的调节灵活有效地修正叶型。气动数值模拟采用的是基于求解二维N-S方程的CFD程序。对NACA叶型的正问题数值优化结果表明以混合遗传算法为基础的优化设计平台是十分有效的。 展开更多
关键词 压气机 ^混合遗传算法^+ ^复合形法+^ 叶型 优化设计
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Integrated logistics facilities network design for 3PLS under uncertainty 被引量:1
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作者 张永 李建 +1 位作者 李旭宏 毛海军 《Journal of Southeast University(English Edition)》 EI CAS 2006年第4期570-576,共7页
According to the operational characteristics of the logistics networks for the third party logistics supplier (3PLS), the forward and reverse logistics networks together for 3PLS under the uncertain environment are ... According to the operational characteristics of the logistics networks for the third party logistics supplier (3PLS), the forward and reverse logistics networks together for 3PLS under the uncertain environment are designed. First, a fuzzy model is proposed by taking multiple customers, multiple commodities, capacitated facility location and integrated logistics facility layout into account. In the model, the fuzzy customer demands and transportation rates are illustrated by triangular fuzzy numbers. Secondly, the fuzzy model is converted into a crisp model by applying fuzzy chance constrained theory and possibility theory, and one hybrid genetic algorithm is designed for the crisp model. Finally, two different examples are designed to illustrate that the model and solution discussed are valid. 展开更多
关键词 third party logistics supplier integrated logistics facilities network design fuzzy chance constrained model hybrid genetic algorithm UNCERTAINTY
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Objective increment based metaheuristic for total flowtime minimization in no-wait flowshops
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作者 朱夏 李小平 王茜 《Journal of Southeast University(English Edition)》 EI CAS 2008年第2期168-173,共6页
To solve the NP-complete no-wait flowshop problems, objective increment properties are analyzed and proved for fundamental operations of heuristics. With these properties, whether a new generated schedule is better or... To solve the NP-complete no-wait flowshop problems, objective increment properties are analyzed and proved for fundamental operations of heuristics. With these properties, whether a new generated schedule is better or worse than the original one is only evaluated by objective increments, instead of completely calculating objective values as the traditional algorithms do, so that the computational time can be considerably reduced. An objective increment-based hybrid genetic algorithm (IGA) is proposed by integrating the genetic algorithm (GA) with an improved various neighborhood search (VNS)as a local search. An initial solution generation heuristic(ISG) is constructed to generate one individual of the initial population. An expectation value-based selection mechanism and a crossover operator are introduced to the mating process. The IGA is compared with the traditional GA and two best-so-far algorithms for the considered problem on 110 benchmark instances. An experimental results show that the IGA outperforms the others in effectiveness although with a little more time consumption. 展开更多
关键词 no-wait flowshops total flowtime objective increment hybrid genetic algorithm
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Bi-level programming model and algorithm for optimizing headway of public transit line
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作者 张健 李文权 《Journal of Southeast University(English Edition)》 EI CAS 2010年第3期471-474,共4页
Due to the fact that headway is a key factor to be considered in bus scheduling, this paper proposes a bi-level programming model for optimizing bus headway in public transit lines. In this model, with the interests o... Due to the fact that headway is a key factor to be considered in bus scheduling, this paper proposes a bi-level programming model for optimizing bus headway in public transit lines. In this model, with the interests of bus companies and passengers in mind, the upper-level model's objective is to minimize the total cost, which is affected by frequency settings, both in time and economy in the transit system. The lower-level model is a transit assignment model used to describe the assignment of passengers' trips to the network based on the optimal bus headway. In order to solve the proposed model, a hybrid genetic algorithm, namely the genetic algorithm and the simulated annealing algorithm (GA-SA), is designed. Finally, the model and the algorithm are tested against the transit data, by taking some of the bus lines of Changzhou city as an example. Results indicate that the proposed model allows supply and demand to be linked, which is reasonable, and the solving algorithm is effective. 展开更多
关键词 HEADWAY bi-level model transit assignment hybrid genetic algorithm
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Study on Multi-stream Heat Exchanger Network Synthesis with Parallel Genetic/Simulated Annealing Algorithm 被引量:13
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作者 魏关锋 姚平经 +1 位作者 LUOXing ROETZELWilfried 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2004年第1期66-77,共12页
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 opt... 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. 展开更多
关键词 multi-stream heat exchanger network synthesis non-isothermal mixing mixed integer nonlinear programming model genetic algorithm simulated annealing algorithm hybrid algorithm
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Search for circular and noncircular critical slip surfaces in slope stability analysis by hybrid genetic algorithm 被引量:8
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作者 朱剑锋 陈昌富 《Journal of Central South University》 SCIE EI CAS 2014年第1期387-397,共11页
A local improvement procedure based on tabu search(TS) was incorporated into a basic genetic algorithm(GA) and a global optimal algorithm,i.e.,hybrid genetic algorithm(HGA) approach was used to search the circular and... A local improvement procedure based on tabu search(TS) was incorporated into a basic genetic algorithm(GA) and a global optimal algorithm,i.e.,hybrid genetic algorithm(HGA) approach was used to search the circular and noncircular slip surfaces associated with their minimum safety factors.The slope safety factors of circular and noncircular critical slip surfaces were calculated by the simplified Bishop method and an improved Morgenstern-Price method which can be conveniently programmed,respectively.Comparisons with other methods were made which indicate the high efficiency and accuracy of the HGA approach.The HGA approach was used to calculate one case example and the results demonstrated its applicability to practical engineering. 展开更多
关键词 SLOPE STABILITY genetic algorithm tabu search algorithm safety factor
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An Improved Hybrid Genetic Algorithm for Chemical Plant Layout Optimization with Novel Non-overlapping and Toxic Gas Dispersion Constraints 被引量:8
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作者 徐圆 王振宇 朱群雄 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2013年第4期412-419,共8页
New approaches for facility distribution in chemical plants are proposed including an improved non-overlapping constraint based on projection relationships of facilities and a novel toxic gas dispersion constraint. In... New approaches for facility distribution in chemical plants are proposed including an improved non-overlapping constraint based on projection relationships of facilities and a novel toxic gas dispersion constraint. In consideration of the large number of variables in the plant layout model, our new method can significantly reduce the number of variables with their own projection relationships. Also, as toxic gas dispersion is a usual incident in a chemical plant, a simple approach to describe the gas leakage is proposed, which can clearly represent the constraints of potential emission source and sitting facilities. For solving the plant layout model, an improved genetic algorithm (GA) based on infeasible solution fix technique is proposed, which improves the globe search ability of GA. The case study and experiment show that a better layout plan can be obtained with our method, and the safety factors such as gas dispersion and minimum distances can be well handled in the solution. 展开更多
关键词 plant layout non-overlapping constraints toxic gas dispersion genetic algorithm
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Optimization of projectile aerodynamic parameters based on hybrid genetic algorithm
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作者 刘霖 田晓丽 +2 位作者 高小东 甘桃元 佘新继 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2015年第4期364-367,共4页
Aerodynamic parameters are important factors that affect projectile flight movement. To obtain accurate aerodynamic parameters, a hybrid genetic algorithm is proposed to identify and optimize the aerodynamic parameter... Aerodynamic parameters are important factors that affect projectile flight movement. To obtain accurate aerodynamic parameters, a hybrid genetic algorithm is proposed to identify and optimize the aerodynamic parameters of projectile. By combining the traditional simulated annealing method that is easy to fall into local optimum solution but hard to get global parameters with the genetic algorithm that has good global optimization ability but slow local optimization ability, the hybrid genetic algo- rithm makes full use of the advantages of the two algorithms for the optimization of projectile aerodynamic parameters. The simulation results show that the hybrid genetic algorithm is better than a single algorithm. 展开更多
关键词 projectile aerodynamic parameters parameter optimization hybrid genetic algorithm
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Inverse procedure for determining model parameter of soils using real-coded genetic algorithm 被引量:3
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作者 李守巨 邵龙潭 +1 位作者 王吉喆 刘迎曦 《Journal of Central South University》 SCIE EI CAS 2012年第6期1764-1770,共7页
The hybrid genetic algorithm is utilized to facilitate model parameter estimation.The tri-dimensional compression tests of soil are performed to supply experimental data for identifying nonlinear constitutive model of... The hybrid genetic algorithm is utilized to facilitate model parameter estimation.The tri-dimensional compression tests of soil are performed to supply experimental data for identifying nonlinear constitutive model of soil.In order to save computing time during parameter inversion,a new procedure to compute the calculated strains is presented by multi-linear simplification approach instead of finite element method(FEM).The real-coded hybrid genetic algorithm is developed by combining normal genetic algorithm with gradient-based optimization algorithm.The numerical and experimental results for conditioned soil are compared.The forecast strains based on identified nonlinear constitutive model of soil agree well with observed ones.The effectiveness and accuracy of proposed parameter estimation approach are validated. 展开更多
关键词 parameter estimation real-coded genetic algorithm tri-dimensional compression test gradient-based optimization
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A ROBUST PHASE-ONLY DIRECT DATA DOMAIN ALGORITHM BASED ON GENERALIZED RAYLEIGH QUOTIENT OPTIMIZATION USING HYBRID GENETIC ALGORITHM 被引量:2
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作者 Shao Wei Qian Zuping Yuan Feng 《Journal of Electronics(China)》 2007年第4期560-566,共7页
A robust phase-only Direct Data Domain Least Squares (D3LS) algorithm based on gen- eralized Rayleigh quotient optimization using hybrid Genetic Algorithm (GA) is presented in this letter. The optimization efficiency ... A robust phase-only Direct Data Domain Least Squares (D3LS) algorithm based on gen- eralized Rayleigh quotient optimization using hybrid Genetic Algorithm (GA) is presented in this letter. The optimization efficiency and computational speed are improved via the hybrid GA com- posed of standard GA and Nelder-Mead simplex algorithms. First, the objective function, with a form of generalized Rayleigh quotient, is derived via the standard D3LS algorithm. It is then taken as a fitness function and the unknown phases of all adaptive weights are taken as decision variables. Then, the nonlinear optimization is performed via the hybrid GA to obtain the optimized solution of phase-only adaptive weights. As a phase-only adaptive algorithm, the proposed algorithm is sim- pler than conventional algorithms when it comes to hardware implementation. Moreover, it proc- esses only a single snapshot data as opposed to forming sample covariance matrix and operating matrix inversion. Simulation results show that the proposed algorithm has a good signal recovery and interferences nulling performance, which are superior to that of the phase-only D3LS algorithm based on standard GA. 展开更多
关键词 Generalized Rayleigh quotient Hybrid genetic algorithm Phase-only optimization Direct Data Domain Least Squares ^(D^3LS) algorithm Nelder-Mead simplex algorithm
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An optimizing algorithm of static task scheduling problem based on hybrid genetic algorithm 被引量:3
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作者 柳玉 Song Jian Wen Jiayan 《High Technology Letters》 EI CAS 2016年第2期170-176,共7页
To reduce resources consumption of parallel computation system, a static task scheduling opti- mization method based on hybrid genetic algorithm is proposed and validated, which can shorten the scheduling length of pa... To reduce resources consumption of parallel computation system, a static task scheduling opti- mization method based on hybrid genetic algorithm is proposed and validated, which can shorten the scheduling length of parallel tasks with precedence constraints. Firstly, the global optimal model and constraints are created to demonstrate the static task scheduling problem in heterogeneous distributed computing systems(HeDCSs). Secondly, the genetic population is coded with matrix and used to search the total available time span of the processors, and then the simulated annealing algorithm is introduced to improve the convergence speed and overcome the problem of easily falling into local minimum point, which exists in the traditional genetic algorithm. Finally, compared to other existed scheduling algorithms such as dynamic level scheduling ( DLS), heterogeneous earliest finish time (HEFr), and longest dynamic critical path( LDCP), the proposed approach does not merely de- crease tasks schedule length, but also achieves the maximal resource utilization of parallel computa- tion system by extensive experiments. 展开更多
关键词 genetic algorithm simulated annealing algorithm parallel computation directedacyelic graph
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The RHSA Strategy for the Allocation of Outbound Containers Based on the Hybrid Genetic Algorithm 被引量:1
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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).Thi... 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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Hybrid genetic algorithm for the optimization of mine ventilation network 被引量:1
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作者 ZHAO Dan LIU Jian +1 位作者 PAN Jing-tao MA Heng 《Journal of Coal Science & Engineering(China)》 2009年第4期389-393,共5页
Used genetic algorithm (GA) to optimize the network of ventilation in order toavoid artificial convergence and speed up the convergence rate to introduce the Powellalgorithm. The Powell algorithm had been integrated i... Used genetic algorithm (GA) to optimize the network of ventilation in order toavoid artificial convergence and speed up the convergence rate to introduce the Powellalgorithm. The Powell algorithm had been integrated into GA. Powell had the effectivecapacity of solving the local optimal solution. Powell and the cross as a method ofchoice, a variation of the parallel operator, can be a better solution to the prematureconvergence of the GA problem. The two methods will be improved to make it an effective combination of hybrid GA called hybrid genetic algorithm (HGA) for the introductionof mine ventilation network optimization and to be used to solve the problem of regulating mine optimization. 展开更多
关键词 HYBRID genetic algorithm(GA) Powell algorithm ventilation net-work optimization
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Groundwater level prediction based on hybrid hierarchy genetic algorithm and RBF neural network 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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A hybrid genetic algorithm for multi-modal image registration
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作者 赵永明 张素 +1 位作者 肖昌炎 陈亚珠 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2006年第1期82-87,共6页
This paper describes a new method for three-dimensional medical image registration. In the interactive image-guided HIFU ( High Intensity Focused Ultrasound) therapy system, a fast and precise localization of the tu... This paper describes a new method for three-dimensional medical image registration. In the interactive image-guided HIFU ( High Intensity Focused Ultrasound) therapy system, a fast and precise localization of the tumor is very important. An automatic system is developed for registering pre-operative MR images with intra-operative ultrasound images based on the vessels visible in both of the modalities. When the MR and the ultrasound images are aligned, the eenterline points of the vessels in the MR image will align with bright intensities in the ultrasound image. The method applies an optimization strategy combining the genetic algorithm with the conjugated gradients algorithm to minimize the objective function. It provides a feasible way of determining the global solution and makes the method robust to local maximum and insensitive to initial position. Two experiments were designed to evaluate the method, and the results show that our method has better registration accuracy and convergence rate than the other two classic algorithms. 展开更多
关键词 image registration genetic algorithm VESSELS TUMOR
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Multi-Period Model of Portfolio Investment and Adjustment Based on Hybrid Genetic Algorithm
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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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A Hybrid Improved Genetic Algorithm and Its Application in Dynamic Optimization Problems of Chemical Processes 被引量:5
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作者 SUN Fan DU Wenli QI Rongbin QIAN Feng ZHONG Weimin 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2013年第2期144-154,共11页
The solutions of dynamic optimization problems are usually very difficult due to their highly nonlinear and multidimensional nature. 13enetic algorithm (GA) has been proved to be a teasibte method when the gradient ... The solutions of dynamic optimization problems are usually very difficult due to their highly nonlinear and multidimensional nature. 13enetic algorithm (GA) has been proved to be a teasibte method when the gradient is difficult to calculate. Its advantage is that the control profiles at all time stages are optimized simultaneously, but its convergence is very slow in the later period of evolution and it is easily trapped in the local optimum. In this study, a hybrid improved genetic algorithm (HIGA) for solving dynamic optimization problems is proposed to overcome these defects. Simplex method (SM) is used to perform the local search in the neighborhood of the optimal solution. By using SM, the ideal searching direction of global optimal solution could be found as soon as possible and the convergence speed of the algorithm is improved. The hybrid algorithm presents some improvements, such as protecting the best individual, accepting immigrations, as well as employing adaptive crossover and Ganssian mutation operators. The efficiency of the proposed algorithm is demonstrated by solving several dynamic optimization problems. At last, HIGA is applied to the optimal production of secreted protein in a fed batch reactor and the optimal feed-rate found by HIGA is effective and relatively stable. 展开更多
关键词 genetic algorithm simplex method dynamic optimization chemical process
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Optimization of Wind-Marine Hybrid Power System Configuration Based on Genetic Algorithm 被引量:1
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作者 SHI Hongda LI Linna ZHAO Chenyu 《Journal of Ocean University of China》 SCIE CAS CSCD 2017年第4期709-715,共7页
Multi-energy power systems can use energy generated from various sources to improve power generation reliability.This paper presents a cost-power generation model of a wind-tide-wave energy hybrid power system for use... Multi-energy power systems can use energy generated from various sources to improve power generation reliability.This paper presents a cost-power generation model of a wind-tide-wave energy hybrid power system for use on a remote island,where the configuration is optimized using a genetic algorithm.A mixed integer programming model is used and a novel object function,including cost and power generation,is proposed to solve the boundary problem caused by existence of two goals.Using this model,the final optimized result is found to have a good fit with local resources. 展开更多
关键词 genetic algorithm cost-power generation function multi-energy system marine energy
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Healing Temperature of Hybrid Structures Based on Genetic Algorithm
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作者 赵中伟 陈志华 刘红波 《Transactions of Tianjin University》 EI CAS 2016年第1期64-71,共8页
The healing temperature of suspen-dome with stacked arches(SDSA)and arch-supported single-layer lattice shell structures was investigated based on the genetic algorithm. The temperature field of arch under solar radia... The healing temperature of suspen-dome with stacked arches(SDSA)and arch-supported single-layer lattice shell structures was investigated based on the genetic algorithm. The temperature field of arch under solar radiation was derived by FLUENT to investigate the influence of solar radiation on the determination of the healing temperature. Moreover, a multi-scale model was established to apply the complex temperature field under solar radiation. The change in the mechanical response of these two kinds of structures with the healing temperature was discussed. It can be concluded that solar radiation has great influence on the healing temperature, and the genetic algorithm can be effectively used in the optimization of the healing temperature for hybrid structures. 展开更多
关键词 healing temperature genetic algorithm solar radiation strain energy multi-scale model multi-point constraint equation
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Elevator Group-Control Policy Based on Neural Network Optimized by Genetic Algorithm 被引量:1
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作者 沈虹 万健如 +2 位作者 张志超 刘英培 李光叶 《Transactions of Tianjin University》 EI CAS 2009年第4期245-248,共4页
Aiming at the diversity and nonlinearity of the elevator system control target, an effective group method based on a hybrid algorithm of genetic algorithm and neural network is presented in this paper. The genetic alg... Aiming at the diversity and nonlinearity of the elevator system control target, an effective group method based on a hybrid algorithm of genetic algorithm and neural network is presented in this paper. The genetic algorithm is used to search the weight of the neural network. At the same time, the multi-objective-based evaluation function is adopted, in which there are three main indicators including the passenger waiting time, car passengers number and the number of stops. Different weights are given to meet the actual needs. The optimal values of the evaluation function are obtained, and the optimal dispatch control of the elevator group control system based on neural network is realized. By analyzing the running of the elevator group control system, all the processes and steps are presented. The validity of the hybrid algorithm is verified by the dynamic imitation performance. 展开更多
关键词 elevator group control genetic algorithm neural network hybrid algorithm
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