We improve the genetic algorithm by combining it with a simulated annealing algorithm. The improved algorithm is used to extract model parameters of SOI MOSFETs, which are fabricated with standard 1.2μm CMOS/SOI tech...We improve the genetic algorithm by combining it with a simulated annealing algorithm. The improved algorithm is used to extract model parameters of SOI MOSFETs, which are fabricated with standard 1.2μm CMOS/SOI technology developed by the Institute of Microelectronics of the Chinese Academy of Sciences. The simulation results using this model are in excellent agreement with experimental results. The precision is improved noticeably compared to commercial software. This method requires neither a deeper understanding of SOl MOSFETs model nor more complex computations than conventional algorithms used by commercial software. Comprehensive verification shows that this model is applicable to a very large range of device sizes.展开更多
Local and global optimization methods are widely used in geophysical inversion but each has its own advantages and disadvantages. The combination of the two methods will make it possible to overcome their weaknesses. ...Local and global optimization methods are widely used in geophysical inversion but each has its own advantages and disadvantages. The combination of the two methods will make it possible to overcome their weaknesses. Based on the simulated annealing genetic algorithm （SAGA） and the simplex algorithm, an efficient and robust 2-D nonlinear method for seismic travel-time inversion is presented in this paper. First we do a global search over a large range by SAGA and then do a rapid local search using the simplex method. A multi-scale tomography method is adopted in order to reduce non-uniqueness. The velocity field is divided into different spatial scales and velocities at the grid nodes are taken as unknown parameters. The model is parameterized by a bi-cubic spline function. The finite-difference method is used to solve the forward problem while the hybrid method combining multi-scale SAGA and simplex algorithms is applied to the inverse problem. The algorithm has been applied to a numerical test and a travel-time perturbation test using an anomalous low-velocity body. For a practical example, it is used in the study of upper crustal velocity structure of the A＇nyemaqen suture zone at the north-east edge of the Qinghai-Tibet Plateau. The model test and practical application both prove that the method is effective and robust.展开更多
Effective temperature level of stream, namely stream pseudo temperature, is determined by its actual temperature and heat transfer temperature difference contribution value. Heat transfer temperature difference con-tr...Effective temperature level of stream, namely stream pseudo temperature, is determined by its actual temperature and heat transfer temperature difference contribution value. Heat transfer temperature difference con-tribution value of a stream depends on its heat transfer film coefficient, cost per unit heat transfer area, actual tem-perature, and so on. In the determination of the suitable heat transfer temperature difference contribution values of the stream, the total annual cost of multistream heat exchanger network (MSHEN) is regarded as an objective func-tion, and genetic/simulated annealing algorithm (GA/SA) is adopted for optimizing the heat transfer temperature difference contribution values of the stream. The stream pseudo temperatures are subsequently obtained. On the ba-sis of stream pseudo temperature, optimized MSHEN can be attained by the temperature-enthalpy (T-H) diagram method. This approach is characterized with fewer decision variables and higher feasibility of solutions. The calcu-lation efficiency of GA/SA can be remarkably enhanced by this approach and more probability is shown in search-ing the global optimum solution. Hence this approach is presented for solving industrial-sized MSHEN which is difficult to deal by traditional algorithm. Moreover, in the optimization of stream heat transfer temperature differ-ence contribution values, the effects of the stream temperature, the heat transfer film coefficient, and the construc-tion material of heat exchangers are considered, therefore this approach can be used to optimize and design heat exchanger network (HEN) with unequal heat transfer film coefficients and different of construction materials. The performance of the proposed approach has been demonstrated with three examples and the obtained solutions are compared with those available in literatures. The results show that the large-scale MSHEN synthesis problems can be solved to obtain good solutions with the modest computational effort.展开更多
Genetic Algorithm (GA) is a biologically inspired technique and widely used to solve numerous combinational optimization problems. It works on a population of individuals, not just one single solution. As a result, it...Genetic Algorithm (GA) is a biologically inspired technique and widely used to solve numerous combinational optimization problems. It works on a population of individuals, not just one single solution. As a result, it avoids converging to the local optimum. However, it takes too much CPU time in the late process of GA. On the other hand, in the late process Simulated Annealing (SA) converges faster than GA but it is easily trapped to local optimum. In this letter, a useful method that unifies GA and SA is introduced, which utilizes the advantage of the global search ability of GA and fast convergence of SA. The experimental results show that the proposed algorithm outperforms GA in terms of CPU time without degradation of performance. It also achieves highly comparable placement cost compared to the state-of-the-art results obtained by Versatile Place and Route (VPR) Tool.展开更多
This paper applies genetic simulated annealing algorithm (SAGA) to solving geometric constraint problems. This method makes full use of the advantages of SAGA and can handle under-/over- constraint problems naturally....This paper applies genetic simulated annealing algorithm (SAGA) to solving geometric constraint problems. This method makes full use of the advantages of SAGA and can handle under-/over- constraint problems naturally. It has advantages (due to its not being sensitive to the initial values) over the Newton-Raphson method, and its yielding of multiple solutions, is an advantage over other optimal methods for multi-solution constraint system. Our experiments have proved the robustness and efficiency of this method.展开更多
The motivation of data mining is how to extract effective information from huge data in very large database. However, some redundant and irrelevant attributes, which result in low performance and high computing comple...The motivation of data mining is how to extract effective information from huge data in very large database. However, some redundant and irrelevant attributes, which result in low performance and high computing complexity, are included in the very large database in general.So, Feature Subset Selection (FSS) becomes one important issue in the field of data mining. In this letter, an FSS model based on the filter approach is built, which uses the simulated annealing genetic algorithm. Experimental results show that convergence and stability of this algorithm are adequately achieved.展开更多
Under the condition of the designated collection ratio and the interfused ratio of mullock, to ensure the least energy consumption, the parameters of collecting head （the feed speed, the axes height of collecting hea...Under the condition of the designated collection ratio and the interfused ratio of mullock, to ensure the least energy consumption, the parameters of collecting head （the feed speed, the axes height of collecting head, and the rotate speed） are chosen as the optimized parameters. According to the force on the cutting pick, the collecting size of the cobalt crust and bedrock and the optimized energy consumption of the collecting head, the optimized design model of collecting head is built. Taking two hundred groups seabed microtopography for grand in the range of depth displacement from 4.5 to 5.5 era, then making use of the improved simulated annealing genetic algorithm （SAGA）, the corresponding optimized result can be obtained. At the same time, in order to speed up the controlling of collecting head, the optimization results are analyzed using the regression analysis method, and the conclusion of the second parameter of the seabed microtopography is drawn.展开更多
A hybrid feature selection and classification strategy was proposed based on the simulated annealing genetic algonthrn and multiple instance learning （MIL）. The band selection method was proposed from subspace decom...A hybrid feature selection and classification strategy was proposed based on the simulated annealing genetic algonthrn and multiple instance learning （MIL）. The band selection method was proposed from subspace decomposition, which combines the simulated annealing algorithm with the genetic algorithm in choosing different cross-over and mutation probabilities, as well as mutation individuals. Then MIL was combined with image segmentation, clustering and support vector machine algorithms to classify hyperspectral image. The experimental results show that this proposed method can get high classification accuracy of 93.13% at small training samples and the weaknesses of the conventional methods are overcome.展开更多
Hidden Maxkov models （HMMs） have been used to model burst error sources of wireless channels. This paper proposes a hybrid method of using genetic algorithm （GA） and simulated annealing （SA） to train HMM for dis...Hidden Maxkov models （HMMs） have been used to model burst error sources of wireless channels. This paper proposes a hybrid method of using genetic algorithm （GA） and simulated annealing （SA） to train HMM for discrete channel modelling. The proposed method is compared with pure GA, and experimental results show that the HMMs trained by the hybrid method can better describe the error sequences due to SA＇s ability of facilitating hill-climbing at the later stage of the search. The burst error statistics of the HMMs trained by the proposed method and the corresponding error sequences are also presented to validate the proposed method.展开更多
We extended an improved version of the discrete particle swarm optimization (DPSO) algorithm proposed by Liao et al.(2007) to solve the dynamic facility layout problem (DFLP). A computational study was performed with ...We extended an improved version of the discrete particle swarm optimization (DPSO) algorithm proposed by Liao et al.(2007) to solve the dynamic facility layout problem (DFLP). A computational study was performed with the existing heuristic algorithms, including the dynamic programming (DP), genetic algorithm (GA), simulated annealing (SA), hybrid ant system (HAS), hybrid simulated annealing (SA-EG), hybrid genetic algorithms (NLGA and CONGA). The proposed DPSO algorithm, SA, HAS, GA, DP, SA-EG, NLGA, and CONGA obtained the best solutions for 33, 24, 20, 10, 12, 20, 5, and 2 of the 48 problems from (Balakrishnan and Cheng, 2000), respectively. These results show that the DPSO is very effective in dealing with the DFLP. The extended DPSO also has very good computational efficiency when the problem size increases.展开更多
The component-based business architecture integration of military information systems is a popu- lar research topic in the field of military operational research. Identifying enterprise-level business components is an...The component-based business architecture integration of military information systems is a popu- lar research topic in the field of military operational research. Identifying enterprise-level business components is an important issue in business architecture integration. Currently used methodologies for business component identification tend to focus on software-level business components, and ignore such enterprise concerns in business architectures as organizations and resources. Moreover, approaches to enterprise-level business component identi- fication have proven laborious. In this study, we propose a novel approach to enterprise-level business component identification by considering overall cohesion, coupling, granularity, maintainability, and reusability. We first define and formulate enterprise-level business components based on the component business model and the Department of Defense Architecture Framework （DoDAF） models. To quantify the indices of business components, we formulate a create, read, update, and delete （CRUD） matrix and use six metrics as criteria. We then formulate business com- ponent identification as a multi：objective optimization problem and solve it by a novel meta-heuristic optimization algorithm called the ＇simulated annealing hybrid genetic algorithm （SHGA）＇. Case studies showed that our approach is more practical and efficient for enterprise-level business component identification than prevalent approaches.展开更多
In this paper,a modified genetic local search algorithm(MGLSA) is proposed.The proposed algorithm is resulted from employing the simulated annealing technique to regulate the variance of the Gaussian mutation of the g...In this paper,a modified genetic local search algorithm(MGLSA) is proposed.The proposed algorithm is resulted from employing the simulated annealing technique to regulate the variance of the Gaussian mutation of the genetic local search algorithm(GLSA).Then,an MGLSA-based inverse algorithm is proposed for magnetic flux leakage(MFL) signal inversion of corrosive flaws,in which the MGLSA is used to solve the optimization problem in the MFL inverse problem.Experimental results demonstrate that the MGLSA-based inverse algorithm is more robust than GLSA-based inverse algorithm in the presence of noise in the measured MFL signals.展开更多
文摘We improve the genetic algorithm by combining it with a simulated annealing algorithm. The improved algorithm is used to extract model parameters of SOI MOSFETs, which are fabricated with standard 1.2μm CMOS/SOI technology developed by the Institute of Microelectronics of the Chinese Academy of Sciences. The simulation results using this model are in excellent agreement with experimental results. The precision is improved noticeably compared to commercial software. This method requires neither a deeper understanding of SOl MOSFETs model nor more complex computations than conventional algorithms used by commercial software. Comprehensive verification shows that this model is applicable to a very large range of device sizes.
基金supported by the National Natural Science Foundation of China (Grant Nos.40334040 and 40974033)the Promoting Foundation for Advanced Persons of Talent of NCWU
文摘Local and global optimization methods are widely used in geophysical inversion but each has its own advantages and disadvantages. The combination of the two methods will make it possible to overcome their weaknesses. Based on the simulated annealing genetic algorithm （SAGA） and the simplex algorithm, an efficient and robust 2-D nonlinear method for seismic travel-time inversion is presented in this paper. First we do a global search over a large range by SAGA and then do a rapid local search using the simplex method. A multi-scale tomography method is adopted in order to reduce non-uniqueness. The velocity field is divided into different spatial scales and velocities at the grid nodes are taken as unknown parameters. The model is parameterized by a bi-cubic spline function. The finite-difference method is used to solve the forward problem while the hybrid method combining multi-scale SAGA and simplex algorithms is applied to the inverse problem. The algorithm has been applied to a numerical test and a travel-time perturbation test using an anomalous low-velocity body. For a practical example, it is used in the study of upper crustal velocity structure of the A＇nyemaqen suture zone at the north-east edge of the Qinghai-Tibet Plateau. The model test and practical application both prove that the method is effective and robust.
基金Supported by the Deutsche Forschungsgemeinschaft (DFG No.RO 294/9).
文摘Effective temperature level of stream, namely stream pseudo temperature, is determined by its actual temperature and heat transfer temperature difference contribution value. Heat transfer temperature difference con-tribution value of a stream depends on its heat transfer film coefficient, cost per unit heat transfer area, actual tem-perature, and so on. In the determination of the suitable heat transfer temperature difference contribution values of the stream, the total annual cost of multistream heat exchanger network (MSHEN) is regarded as an objective func-tion, and genetic/simulated annealing algorithm (GA/SA) is adopted for optimizing the heat transfer temperature difference contribution values of the stream. The stream pseudo temperatures are subsequently obtained. On the ba-sis of stream pseudo temperature, optimized MSHEN can be attained by the temperature-enthalpy (T-H) diagram method. This approach is characterized with fewer decision variables and higher feasibility of solutions. The calcu-lation efficiency of GA/SA can be remarkably enhanced by this approach and more probability is shown in search-ing the global optimum solution. Hence this approach is presented for solving industrial-sized MSHEN which is difficult to deal by traditional algorithm. Moreover, in the optimization of stream heat transfer temperature differ-ence contribution values, the effects of the stream temperature, the heat transfer film coefficient, and the construc-tion material of heat exchangers are considered, therefore this approach can be used to optimize and design heat exchanger network (HEN) with unequal heat transfer film coefficients and different of construction materials. The performance of the proposed approach has been demonstrated with three examples and the obtained solutions are compared with those available in literatures. The results show that the large-scale MSHEN synthesis problems can be solved to obtain good solutions with the modest computational effort.
基金Supported by School of Engineering, Napier University, United Kingdom, and partially supported by the National Natural Science Foundation of China (No.60273093).
文摘Genetic Algorithm (GA) is a biologically inspired technique and widely used to solve numerous combinational optimization problems. It works on a population of individuals, not just one single solution. As a result, it avoids converging to the local optimum. However, it takes too much CPU time in the late process of GA. On the other hand, in the late process Simulated Annealing (SA) converges faster than GA but it is easily trapped to local optimum. In this letter, a useful method that unifies GA and SA is introduced, which utilizes the advantage of the global search ability of GA and fast convergence of SA. The experimental results show that the proposed algorithm outperforms GA in terms of CPU time without degradation of performance. It also achieves highly comparable placement cost compared to the state-of-the-art results obtained by Versatile Place and Route (VPR) Tool.
文摘This paper applies genetic simulated annealing algorithm (SAGA) to solving geometric constraint problems. This method makes full use of the advantages of SAGA and can handle under-/over- constraint problems naturally. It has advantages (due to its not being sensitive to the initial values) over the Newton-Raphson method, and its yielding of multiple solutions, is an advantage over other optimal methods for multi-solution constraint system. Our experiments have proved the robustness and efficiency of this method.
基金Supported by the Project of the Science and Technology Plan of Chongqing City
文摘The motivation of data mining is how to extract effective information from huge data in very large database. However, some redundant and irrelevant attributes, which result in low performance and high computing complexity, are included in the very large database in general.So, Feature Subset Selection (FSS) becomes one important issue in the field of data mining. In this letter, an FSS model based on the filter approach is built, which uses the simulated annealing genetic algorithm. Experimental results show that convergence and stability of this algorithm are adequately achieved.
基金Project(50875265) supported by the National Natural Science Foundation of ChinaProject(20080440992) supported by the Postdoctoral Science Foundation of ChinaProject(2009SK3159) supported by the Technology Support Plan of Hunan Province,China
文摘Under the condition of the designated collection ratio and the interfused ratio of mullock, to ensure the least energy consumption, the parameters of collecting head （the feed speed, the axes height of collecting head, and the rotate speed） are chosen as the optimized parameters. According to the force on the cutting pick, the collecting size of the cobalt crust and bedrock and the optimized energy consumption of the collecting head, the optimized design model of collecting head is built. Taking two hundred groups seabed microtopography for grand in the range of depth displacement from 4.5 to 5.5 era, then making use of the improved simulated annealing genetic algorithm （SAGA）, the corresponding optimized result can be obtained. At the same time, in order to speed up the controlling of collecting head, the optimization results are analyzed using the regression analysis method, and the conclusion of the second parameter of the seabed microtopography is drawn.
文摘A hybrid feature selection and classification strategy was proposed based on the simulated annealing genetic algonthrn and multiple instance learning （MIL）. The band selection method was proposed from subspace decomposition, which combines the simulated annealing algorithm with the genetic algorithm in choosing different cross-over and mutation probabilities, as well as mutation individuals. Then MIL was combined with image segmentation, clustering and support vector machine algorithms to classify hyperspectral image. The experimental results show that this proposed method can get high classification accuracy of 93.13% at small training samples and the weaknesses of the conventional methods are overcome.
文摘Hidden Maxkov models （HMMs） have been used to model burst error sources of wireless channels. This paper proposes a hybrid method of using genetic algorithm （GA） and simulated annealing （SA） to train HMM for discrete channel modelling. The proposed method is compared with pure GA, and experimental results show that the HMMs trained by the hybrid method can better describe the error sequences due to SA＇s ability of facilitating hill-climbing at the later stage of the search. The burst error statistics of the HMMs trained by the proposed method and the corresponding error sequences are also presented to validate the proposed method.
文摘We extended an improved version of the discrete particle swarm optimization (DPSO) algorithm proposed by Liao et al.(2007) to solve the dynamic facility layout problem (DFLP). A computational study was performed with the existing heuristic algorithms, including the dynamic programming (DP), genetic algorithm (GA), simulated annealing (SA), hybrid ant system (HAS), hybrid simulated annealing (SA-EG), hybrid genetic algorithms (NLGA and CONGA). The proposed DPSO algorithm, SA, HAS, GA, DP, SA-EG, NLGA, and CONGA obtained the best solutions for 33, 24, 20, 10, 12, 20, 5, and 2 of the 48 problems from (Balakrishnan and Cheng, 2000), respectively. These results show that the DPSO is very effective in dealing with the DFLP. The extended DPSO also has very good computational efficiency when the problem size increases.
基金Project supported by the National.Natural Science Foundation of China （No. 71571189）
文摘The component-based business architecture integration of military information systems is a popu- lar research topic in the field of military operational research. Identifying enterprise-level business components is an important issue in business architecture integration. Currently used methodologies for business component identification tend to focus on software-level business components, and ignore such enterprise concerns in business architectures as organizations and resources. Moreover, approaches to enterprise-level business component identi- fication have proven laborious. In this study, we propose a novel approach to enterprise-level business component identification by considering overall cohesion, coupling, granularity, maintainability, and reusability. We first define and formulate enterprise-level business components based on the component business model and the Department of Defense Architecture Framework （DoDAF） models. To quantify the indices of business components, we formulate a create, read, update, and delete （CRUD） matrix and use six metrics as criteria. We then formulate business com- ponent identification as a multi：objective optimization problem and solve it by a novel meta-heuristic optimization algorithm called the ＇simulated annealing hybrid genetic algorithm （SHGA）＇. Case studies showed that our approach is more practical and efficient for enterprise-level business component identification than prevalent approaches.
基金the Innovation Program of ShanghaiMunicipal Education Commission(No.09YZ340)the Leading Academic Discipline Project of ShanghaiMunicipal Education Commission(No.J51301)+2 种基金the Special Scientific Research Project of Scienceand Technology Commission of Shanghai Municipality(No.08240512000)the Shanghai Municipal EducationCommission Scientific Foundation Projection(No.06LZ009)the Shanghai Key Science and TechnologyProject(No.061612041)
文摘In this paper,a modified genetic local search algorithm(MGLSA) is proposed.The proposed algorithm is resulted from employing the simulated annealing technique to regulate the variance of the Gaussian mutation of the genetic local search algorithm(GLSA).Then,an MGLSA-based inverse algorithm is proposed for magnetic flux leakage(MFL) signal inversion of corrosive flaws,in which the MGLSA is used to solve the optimization problem in the MFL inverse problem.Experimental results demonstrate that the MGLSA-based inverse algorithm is more robust than GLSA-based inverse algorithm in the presence of noise in the measured MFL signals.
