The gate assignment at an airport is one of the major activities in airport operations.With the increase of passenger traffic volumes and the number of flights, the complexity of this task and the factors to be consid...The gate assignment at an airport is one of the major activities in airport operations.With the increase of passenger traffic volumes and the number of flights, the complexity of this task and the factors to be considered have increased significantly, and an efficient gate utilizationhas received considerable attention. For overcoming the shortcomings of previous gate assignmentapproaches, this paper presents a partial parallel gate assignment approach, by which more factorsconcerning aircraft and gates can be collsidered at the same time. This paper also presents themethod of using a knowledge-based system combined with a mathematical programming method forgetting an optimized feasible assignment solution. By this way, it is more easily to get the solutionthat satisfies both the static and dynamic situations,and thus it may adapt well to meet the needsof actual use to rea-time operations. An experimental prototype has been implemented, and a casestudy is presented at the end of the paper.展开更多
To solve the problem of advanced digital manufacturing technology in the practical application, a knowledge engineering technology was introduced into the computer numerical control(CNC) programming. The knowledge acq...To solve the problem of advanced digital manufacturing technology in the practical application, a knowledge engineering technology was introduced into the computer numerical control(CNC) programming. The knowledge acquisition, knowledge representation and reasoning used in CNC programming were researched. The CNC programming system functional architecture of impeller parts based on knowledge based engineering(KBE) was constructed. The structural model of the general knowledge-based system(KBS) was also constructed. The KBS of CNC programming system was established through synthesizing database technology and knowledge base theory. And in the context of corporate needs, based on the knowledge-driven manufacturing platform(i.e. UG CAD/CAM), VC++6.0 and UG/Open, the KBS and UG CAD/CAM were integrated seamlessly and the intelligent CNC programming KBE system for the impeller parts was developed by integrating KBE and UG CAD/CAM system. A method to establish standard process templates was proposed, so as to develop the intelligent CNC programming system in which CNC machining process and process parameters were standardized by using this KBE system. For the impeller parts processing, the method applied in the development of the prototype system is proven to be viable, feasible and practical.展开更多
This paper aims to explore the ability of genetic programming(GP)to achieve the intelligent prediction of tunnelling-induced building deformation considering the multifactor impact.A total of 1099 groups of data obtai...This paper aims to explore the ability of genetic programming(GP)to achieve the intelligent prediction of tunnelling-induced building deformation considering the multifactor impact.A total of 1099 groups of data obtained from 22 geotechnical centrifuge tests are used for model development and analysis using GP.Tunnel volume loss,building eccentricity,soil density,building transverse width,building shear stiffness and building load are selected as the inputs,and shear distortion is selected as the output.Results suggest that the proposed intelligent prediction model is capable of providing a reasonable and accurate prediction of framed building shear distortion due to tunnel construction with realistic conditions,highlighting the important roles of shear stiffness of framed buildings and the pressure beneath the foundation on structural deformation.It has been proven that the proposed model is efficient and feasible to analyze relevant engineering problems by parametric analysis and comparative analysis.The findings demonstrate the great potential of GP approaches in predicting building distortion caused by tunnelling.The proposed equation can be used for the quick and intelligent prediction of tunnelling induced building deformation,providing valuable guidance for the practical design and risk assessment of urban tunnel construction projects.展开更多
Peta-scale high-perfomlance computing systems are increasingly built with heterogeneous CPU and GPU nodes to achieve higher power efficiency and computation throughput. While providing unprecedented capabilities to co...Peta-scale high-perfomlance computing systems are increasingly built with heterogeneous CPU and GPU nodes to achieve higher power efficiency and computation throughput. While providing unprecedented capabilities to conduct computational experiments of historic significance, these systems are presently difficult to program. The users, who are domain experts rather than computer experts, prefer to use programming models closer to their domains （e.g., physics and biology） rather than MPI and OpenME This has led the development of domain-specific programming that provides domain-specific programming interfaces but abstracts away some performance-critical architecture details. Based on experience in designing large-scale computing systems, a hybrid programming framework for scientific computing on heterogeneous architectures is proposed in this work. Its design philosophy is to provide a collaborative mechanism for domain experts and computer experts so that both domain-specific knowledge and performance-critical architecture details can be adequately exploited. Two real-world scientific applications have been evaluated on TH-IA, a peta-scale CPU-GPU heterogeneous system that is currently the 5th fastest supercomputer in the world. The experimental results show that the proposed framework is well suited for developing large-scale scientific computing applications on peta-scale heterogeneous CPU/GPU systems.展开更多
Because of an unfortunate mistake during the production of this article,the Acknowledgements have been omitted.The Acknowledgements are added as follows:Sasan YAZDANI would like to thank the Scientific and Technologic...Because of an unfortunate mistake during the production of this article,the Acknowledgements have been omitted.The Acknowledgements are added as follows:Sasan YAZDANI would like to thank the Scientific and Technological Research Council of Turkey(TÜB˙ITAK)for receiving financial support for this work through the 2221 Fellowship Program for Visiting Scientists and Scientists on Sabbatical Leave(Grant ID:E 21514107-115.02-228864).Sasan YAZDANI also expresses his gratitude to Sahand University of Technology for granting him sabbatical leave to facilitate the completion of this research.展开更多
International freedom of the air(traffic rights)is a key resource for airlines to carry out international air transport business.An efficient and reasonable traffic right resource allocation within a country between a...International freedom of the air(traffic rights)is a key resource for airlines to carry out international air transport business.An efficient and reasonable traffic right resource allocation within a country between airlines can affect the quality of a country’s participation in international air transport.In this paper,a multi-objective mixed-integer programming model for traffic rights resource allocation is developed to minimize passenger travel mileages and maximize the number of traffic rights resources allocated to hub airports and competitive carriers.A hybrid heuristic algorithm combining the genetic algorithm and the variable neighborhood search is devised to solve the model.The results show that the optimal allocation scheme aligns with the principle of fairness,indicating that the proposed model can play a certain guiding role in and provide an innovative perspective on traffic rights resource allocation in various countries.展开更多
In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of t...In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of the three-dimensional attack area model,restrict their practical applications.To address these issues,an improved backtracking algorithm is proposed to improve calculation efficiency.A significant reduction in solution time and maintenance of accuracy in the three-dimensional attack area are achieved by using the proposed algorithm.Furthermore,the age-layered population structure genetic programming(ALPS-GP)algorithm is introduced to determine an analytical polynomial model of the three-dimensional attack area,considering real-time requirements.The accuracy of the polynomial model is enhanced through the coefficient correction using an improved gradient descent algorithm.The study reveals a remarkable combination of high accuracy and efficient real-time computation,with a mean error of 91.89 m using the analytical polynomial model of the three-dimensional attack area solved in just 10^(-4)s,thus meeting the requirements of real-time combat scenarios.展开更多
Complex multi-area collaborative coverage path planning in dynamic environments poses a significant challenge for multi-fixed-wing UAVs(multi-UAV).This study establishes a comprehensive framework that incorporates UAV...Complex multi-area collaborative coverage path planning in dynamic environments poses a significant challenge for multi-fixed-wing UAVs(multi-UAV).This study establishes a comprehensive framework that incorporates UAV capabilities,terrain,complex areas,and mission dynamics.A novel dynamic collaborative path planning algorithm is introduced,designed to ensure complete coverage of designated areas.This algorithm meticulously optimizes the operation,entry,and transition paths for each UAV,while also establishing evaluation metrics to refine coverage sequences for each area.Additionally,a three-dimensional path is computed utilizing an altitude descent method,effectively integrating twodimensional coverage paths with altitude constraints.The efficacy of the proposed approach is validated through digital simulations and mixed-reality semi-physical experiments across a variety of dynamic scenarios,including both single-area and multi-area coverage by multi-UAV.Results show that the coverage paths generated by this method significantly reduce both computation time and path length,providing a reliable solution for dynamic multi-UAV mission planning in semi-physical environments.展开更多
The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a nove...The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a novel delivery mode.Spatiotemporal collaboration,along with energy consumption with payload and wind conditions play important roles in delivery route planning.This paper introduces the traveling salesman problem with time window and onboard UAV(TSPTWOUAV)and emphasizes the consideration of real-world scenarios,focusing on time collaboration and energy consumption with wind and payload.To address this,a mixed integer linear programming(MILP)model is formulated to minimize the energy consumption costs of vehicle and UAV.Furthermore,an adaptive large neighborhood search(ALNS)algorithm is applied to identify high-quality solutions efficiently.The effectiveness of the proposed model and algorithm is validated through numerical tests on real geographic instances and sensitivity analysis of key parameters is conducted.展开更多
大多数基于深度学习技术的视觉设备都配备了图像信号处理(Image Signal Processing, ISP)过程以实现RAW数据到RGB图像的转换,同时集成数据预处理过程以完成高效的图像处理。该文在同时考虑ISP和数据预处理过程影响基础上,搭建了深度学...大多数基于深度学习技术的视觉设备都配备了图像信号处理(Image Signal Processing, ISP)过程以实现RAW数据到RGB图像的转换,同时集成数据预处理过程以完成高效的图像处理。该文在同时考虑ISP和数据预处理过程影响基础上,搭建了深度学习视觉应用实验平台,提出针对ISP过程的图像缩放攻击,即精心制作对抗RAW经过ISP过程得到攻击图像,一旦缩放到特定尺寸就会呈现出完全不同的样貌。由于所提出的攻击是由基于ISP过程的梯度驱动的,因此构建了一个等效模型来学习目标ISP的转换过程,利用等效模型的近似梯度来发动攻击。该攻击平台的构建涵盖了深度学习算法、图像处理及对抗攻击优化等内容,有助于学生深入学习和理解基于深度学习视觉应用的任务处理原理以及深度学习模型的弱点,培养学生针对复杂算法问题的创新与实践能力。展开更多
Agent-oriented programming (AOP) is a framework to develop agents, and it aims to link the gap betweentheory and practical in agent research. The core of an AOP framework is its language and semantics. In this paper,w...Agent-oriented programming (AOP) is a framework to develop agents, and it aims to link the gap betweentheory and practical in agent research. The core of an AOP framework is its language and semantics. In this paper,we propose the necessary properties which agents should have, and then give a summary and analysis about differentAOP languages based on these properties.展开更多
A novel chaotic search method is proposed,and a hybrid algorithm combining particle swarm optimization(PSO) with this new method,called CLSPSO,is put forward to solve 14 integer and mixed integer programming problems....A novel chaotic search method is proposed,and a hybrid algorithm combining particle swarm optimization(PSO) with this new method,called CLSPSO,is put forward to solve 14 integer and mixed integer programming problems.The performances of CLSPSO are compared with those of other five hybrid algorithms combining PSO with chaotic search methods.Experimental results indicate that in terms of robustness and final convergence speed,CLSPSO is better than other five algorithms in solving many of these problems.Furthermore,CLSPSO exhibits good performance in solving two high-dimensional problems,and it finds better solutions than the known ones.A performance index(PI) is introduced to fairly compare the above six algorithms,and the obtained values of(PI) in three cases demonstrate that CLSPSO is superior to all the other five algorithms under the same conditions.展开更多
An integer linear bilevel programming problem is firstly transformed into a binary linear bilevel programming problem, and then converted into a single-level binary implicit programming. An orthogonal genetic algorith...An integer linear bilevel programming problem is firstly transformed into a binary linear bilevel programming problem, and then converted into a single-level binary implicit programming. An orthogonal genetic algorithm is developed for solving the binary linear implicit programming problem based on the orthogonal design. The orthogonal design with the factor analysis, an experimental design method is applied to the genetic algorithm to make the algorithm more robust, statistical y sound and quickly convergent. A crossover operator formed by the orthogonal array and the factor analysis is presented. First, this crossover operator can generate a smal but representative sample of points as offspring. After al of the better genes of these offspring are selected, a best combination among these offspring is then generated. The simulation results show the effectiveness of the proposed algorithm.展开更多
An improved genetic algorithm（IGA） based on a novel selection strategy to handle nonlinear programming problems is proposed.Each individual in selection process is represented as a three-dimensional feature vector w...An improved genetic algorithm（IGA） based on a novel selection strategy to handle nonlinear programming problems is proposed.Each individual in selection process is represented as a three-dimensional feature vector which is composed of objective function value,the degree of constraints violations and the number of constraints violations.It is easy to distinguish excellent individuals from general individuals by using an individuals＇ feature vector.Additionally,a local search（LS） process is incorporated into selection operation so as to find feasible solutions located in the neighboring areas of some infeasible solutions.The combination of IGA and LS should offer the advantage of both the quality of solutions and diversity of solutions.Experimental results over a set of benchmark problems demonstrate that IGA has better performance than other algorithms.展开更多
文摘The gate assignment at an airport is one of the major activities in airport operations.With the increase of passenger traffic volumes and the number of flights, the complexity of this task and the factors to be considered have increased significantly, and an efficient gate utilizationhas received considerable attention. For overcoming the shortcomings of previous gate assignmentapproaches, this paper presents a partial parallel gate assignment approach, by which more factorsconcerning aircraft and gates can be collsidered at the same time. This paper also presents themethod of using a knowledge-based system combined with a mathematical programming method forgetting an optimized feasible assignment solution. By this way, it is more easily to get the solutionthat satisfies both the static and dynamic situations,and thus it may adapt well to meet the needsof actual use to rea-time operations. An experimental prototype has been implemented, and a casestudy is presented at the end of the paper.
基金Project(12ZT14)supported by the Natural Science Foundation of Shanghai Municipal Education Commission,China
文摘To solve the problem of advanced digital manufacturing technology in the practical application, a knowledge engineering technology was introduced into the computer numerical control(CNC) programming. The knowledge acquisition, knowledge representation and reasoning used in CNC programming were researched. The CNC programming system functional architecture of impeller parts based on knowledge based engineering(KBE) was constructed. The structural model of the general knowledge-based system(KBS) was also constructed. The KBS of CNC programming system was established through synthesizing database technology and knowledge base theory. And in the context of corporate needs, based on the knowledge-driven manufacturing platform(i.e. UG CAD/CAM), VC++6.0 and UG/Open, the KBS and UG CAD/CAM were integrated seamlessly and the intelligent CNC programming KBE system for the impeller parts was developed by integrating KBE and UG CAD/CAM system. A method to establish standard process templates was proposed, so as to develop the intelligent CNC programming system in which CNC machining process and process parameters were standardized by using this KBE system. For the impeller parts processing, the method applied in the development of the prototype system is proven to be viable, feasible and practical.
基金Projects(52108364,52278398)supported by the National Natural Science Foundation of ChinaProject(211179)supported by the Royal Society,UK+1 种基金Project(22CX06051A)supported by the Independent Innovation Research Plan Project of China University of Petroleum(East China)Project(ZR2023QE004)supported by the Shandong Provincial Natural Science Foundation,China。
文摘This paper aims to explore the ability of genetic programming(GP)to achieve the intelligent prediction of tunnelling-induced building deformation considering the multifactor impact.A total of 1099 groups of data obtained from 22 geotechnical centrifuge tests are used for model development and analysis using GP.Tunnel volume loss,building eccentricity,soil density,building transverse width,building shear stiffness and building load are selected as the inputs,and shear distortion is selected as the output.Results suggest that the proposed intelligent prediction model is capable of providing a reasonable and accurate prediction of framed building shear distortion due to tunnel construction with realistic conditions,highlighting the important roles of shear stiffness of framed buildings and the pressure beneath the foundation on structural deformation.It has been proven that the proposed model is efficient and feasible to analyze relevant engineering problems by parametric analysis and comparative analysis.The findings demonstrate the great potential of GP approaches in predicting building distortion caused by tunnelling.The proposed equation can be used for the quick and intelligent prediction of tunnelling induced building deformation,providing valuable guidance for the practical design and risk assessment of urban tunnel construction projects.
基金Project(61170049) supported by the National Natural Science Foundation of ChinaProject(2012AA010903) supported by the National High Technology Research and Development Program of China
文摘Peta-scale high-perfomlance computing systems are increasingly built with heterogeneous CPU and GPU nodes to achieve higher power efficiency and computation throughput. While providing unprecedented capabilities to conduct computational experiments of historic significance, these systems are presently difficult to program. The users, who are domain experts rather than computer experts, prefer to use programming models closer to their domains （e.g., physics and biology） rather than MPI and OpenME This has led the development of domain-specific programming that provides domain-specific programming interfaces but abstracts away some performance-critical architecture details. Based on experience in designing large-scale computing systems, a hybrid programming framework for scientific computing on heterogeneous architectures is proposed in this work. Its design philosophy is to provide a collaborative mechanism for domain experts and computer experts so that both domain-specific knowledge and performance-critical architecture details can be adequately exploited. Two real-world scientific applications have been evaluated on TH-IA, a peta-scale CPU-GPU heterogeneous system that is currently the 5th fastest supercomputer in the world. The experimental results show that the proposed framework is well suited for developing large-scale scientific computing applications on peta-scale heterogeneous CPU/GPU systems.
基金Supported by National High Technology Research and Development Program of China （863 Program） （2006AA04Z183）, National Nat- ural Science Foundation of China （60621001, 60534010, 60572070, 60774048, 60728307）, and the Program for Changjiang Scholars and Innovative Research Groups of China （60728307, 4031002）
文摘Because of an unfortunate mistake during the production of this article,the Acknowledgements have been omitted.The Acknowledgements are added as follows:Sasan YAZDANI would like to thank the Scientific and Technological Research Council of Turkey(TÜB˙ITAK)for receiving financial support for this work through the 2221 Fellowship Program for Visiting Scientists and Scientists on Sabbatical Leave(Grant ID:E 21514107-115.02-228864).Sasan YAZDANI also expresses his gratitude to Sahand University of Technology for granting him sabbatical leave to facilitate the completion of this research.
基金supported by the National Natural Science Foundation of Chinathe Civil Aviation Administration of China (U2333206).
文摘International freedom of the air(traffic rights)is a key resource for airlines to carry out international air transport business.An efficient and reasonable traffic right resource allocation within a country between airlines can affect the quality of a country’s participation in international air transport.In this paper,a multi-objective mixed-integer programming model for traffic rights resource allocation is developed to minimize passenger travel mileages and maximize the number of traffic rights resources allocated to hub airports and competitive carriers.A hybrid heuristic algorithm combining the genetic algorithm and the variable neighborhood search is devised to solve the model.The results show that the optimal allocation scheme aligns with the principle of fairness,indicating that the proposed model can play a certain guiding role in and provide an innovative perspective on traffic rights resource allocation in various countries.
基金National Natural Science Foundation of China(62373187)Forward-looking Layout Special Projects(ILA220591A22)。
文摘In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of the three-dimensional attack area model,restrict their practical applications.To address these issues,an improved backtracking algorithm is proposed to improve calculation efficiency.A significant reduction in solution time and maintenance of accuracy in the three-dimensional attack area are achieved by using the proposed algorithm.Furthermore,the age-layered population structure genetic programming(ALPS-GP)algorithm is introduced to determine an analytical polynomial model of the three-dimensional attack area,considering real-time requirements.The accuracy of the polynomial model is enhanced through the coefficient correction using an improved gradient descent algorithm.The study reveals a remarkable combination of high accuracy and efficient real-time computation,with a mean error of 91.89 m using the analytical polynomial model of the three-dimensional attack area solved in just 10^(-4)s,thus meeting the requirements of real-time combat scenarios.
基金National Natural Science Foundation of China(Grant No.52472417)to provide fund for conducting experiments.
文摘Complex multi-area collaborative coverage path planning in dynamic environments poses a significant challenge for multi-fixed-wing UAVs(multi-UAV).This study establishes a comprehensive framework that incorporates UAV capabilities,terrain,complex areas,and mission dynamics.A novel dynamic collaborative path planning algorithm is introduced,designed to ensure complete coverage of designated areas.This algorithm meticulously optimizes the operation,entry,and transition paths for each UAV,while also establishing evaluation metrics to refine coverage sequences for each area.Additionally,a three-dimensional path is computed utilizing an altitude descent method,effectively integrating twodimensional coverage paths with altitude constraints.The efficacy of the proposed approach is validated through digital simulations and mixed-reality semi-physical experiments across a variety of dynamic scenarios,including both single-area and multi-area coverage by multi-UAV.Results show that the coverage paths generated by this method significantly reduce both computation time and path length,providing a reliable solution for dynamic multi-UAV mission planning in semi-physical environments.
基金Fundamental Research Funds for the Central Universities(2024JBZX038)National Natural Science F oundation of China(62076023)。
文摘The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a novel delivery mode.Spatiotemporal collaboration,along with energy consumption with payload and wind conditions play important roles in delivery route planning.This paper introduces the traveling salesman problem with time window and onboard UAV(TSPTWOUAV)and emphasizes the consideration of real-world scenarios,focusing on time collaboration and energy consumption with wind and payload.To address this,a mixed integer linear programming(MILP)model is formulated to minimize the energy consumption costs of vehicle and UAV.Furthermore,an adaptive large neighborhood search(ALNS)algorithm is applied to identify high-quality solutions efficiently.The effectiveness of the proposed model and algorithm is validated through numerical tests on real geographic instances and sensitivity analysis of key parameters is conducted.
文摘大多数基于深度学习技术的视觉设备都配备了图像信号处理(Image Signal Processing, ISP)过程以实现RAW数据到RGB图像的转换,同时集成数据预处理过程以完成高效的图像处理。该文在同时考虑ISP和数据预处理过程影响基础上,搭建了深度学习视觉应用实验平台,提出针对ISP过程的图像缩放攻击,即精心制作对抗RAW经过ISP过程得到攻击图像,一旦缩放到特定尺寸就会呈现出完全不同的样貌。由于所提出的攻击是由基于ISP过程的梯度驱动的,因此构建了一个等效模型来学习目标ISP的转换过程,利用等效模型的近似梯度来发动攻击。该攻击平台的构建涵盖了深度学习算法、图像处理及对抗攻击优化等内容,有助于学生深入学习和理解基于深度学习视觉应用的任务处理原理以及深度学习模型的弱点,培养学生针对复杂算法问题的创新与实践能力。
文摘Agent-oriented programming (AOP) is a framework to develop agents, and it aims to link the gap betweentheory and practical in agent research. The core of an AOP framework is its language and semantics. In this paper,we propose the necessary properties which agents should have, and then give a summary and analysis about differentAOP languages based on these properties.
基金Projects(50275150,61173052) supported by the National Natural Science Foundation of ChinaProject(14FJ3112) supported by the Planned Science and Technology of Hunan Province,ChinaProject(14B033) supported by Scientific Research Fund Education Department of Hunan Province,China
文摘A novel chaotic search method is proposed,and a hybrid algorithm combining particle swarm optimization(PSO) with this new method,called CLSPSO,is put forward to solve 14 integer and mixed integer programming problems.The performances of CLSPSO are compared with those of other five hybrid algorithms combining PSO with chaotic search methods.Experimental results indicate that in terms of robustness and final convergence speed,CLSPSO is better than other five algorithms in solving many of these problems.Furthermore,CLSPSO exhibits good performance in solving two high-dimensional problems,and it finds better solutions than the known ones.A performance index(PI) is introduced to fairly compare the above six algorithms,and the obtained values of(PI) in three cases demonstrate that CLSPSO is superior to all the other five algorithms under the same conditions.
基金supported by the Fundamental Research Funds for the Central Universities(K50511700004)the Natural Science Basic Research Plan in Shaanxi Province of China(2013JM1022)
文摘An integer linear bilevel programming problem is firstly transformed into a binary linear bilevel programming problem, and then converted into a single-level binary implicit programming. An orthogonal genetic algorithm is developed for solving the binary linear implicit programming problem based on the orthogonal design. The orthogonal design with the factor analysis, an experimental design method is applied to the genetic algorithm to make the algorithm more robust, statistical y sound and quickly convergent. A crossover operator formed by the orthogonal array and the factor analysis is presented. First, this crossover operator can generate a smal but representative sample of points as offspring. After al of the better genes of these offspring are selected, a best combination among these offspring is then generated. The simulation results show the effectiveness of the proposed algorithm.
基金supported by the National Natural Science Foundation of China (60632050)National Basic Research Program of Jiangsu Province University (08KJB520003)
文摘An improved genetic algorithm（IGA） based on a novel selection strategy to handle nonlinear programming problems is proposed.Each individual in selection process is represented as a three-dimensional feature vector which is composed of objective function value,the degree of constraints violations and the number of constraints violations.It is easy to distinguish excellent individuals from general individuals by using an individuals＇ feature vector.Additionally,a local search（LS） process is incorporated into selection operation so as to find feasible solutions located in the neighboring areas of some infeasible solutions.The combination of IGA and LS should offer the advantage of both the quality of solutions and diversity of solutions.Experimental results over a set of benchmark problems demonstrate that IGA has better performance than other algorithms.
