An improved ant colony optimization （ACO） algorithm is utilized in cell scheduling of the flexible manufaturing process for considering the instrument constraint, manufacturing cost and time. Firstly, the initial we...An improved ant colony optimization （ACO） algorithm is utilized in cell scheduling of the flexible manufaturing process for considering the instrument constraint, manufacturing cost and time. Firstly, the initial weighted directional diagram is set up. Secondly, the algorithm based on the dynamic pheromone updating ensures the quick convergence and the optimal solution, thus improving the feasibility and the stability of the schedule system. Aiming at reducing collaboration with external partners, decreasing the total cost and balancing the production process, the algorithm is efficient in supporting the management process of the manufacturing cell and in strengthening the information arrangement capabitity of the scheduling system. Finally, experimental results of the improved algorithm are compared with those of other algorithms.展开更多
Due to the stubborn nature of dynamic job shop scheduling problem,a novel ant colony coordination mechanism is proposed in this paper to search for an optimal schedule in dynamic environment.In ant colony coordination...Due to the stubborn nature of dynamic job shop scheduling problem,a novel ant colony coordination mechanism is proposed in this paper to search for an optimal schedule in dynamic environment.In ant colony coordination mechanism,the dynamic job shop is composed of several autonomous ants.These ants coordinate with each other by simulating the ant foraging behavior of spreading pheromone on the trails,by which they can make information available globally,and further more guide ants make optimal decisions.The proposed mechanism is tested by several instances and the results confirm the validity of it.展开更多
Performance of the Adaptive Coding and Modulation(ACM) strongly depends on the retrieved Channel State Information(CSI),which can be obtained using the channel estimation techniques relying on pilot symbol transmissio...Performance of the Adaptive Coding and Modulation(ACM) strongly depends on the retrieved Channel State Information(CSI),which can be obtained using the channel estimation techniques relying on pilot symbol transmission.Earlier analysis of methods of pilot-aided channel estimation for ACM systems were relatively little.In this paper,we investigate the performance of CSI prediction using the Minimum Mean Square Error(MMSE)channel estimator for an ACM system.To solve the two problems of MMSE:high computational operations and oversimplified assumption,we then propose the Low-Complexity schemes(LC-MMSE and Recursion LC-MMSE(R-LC-MMSE)).Computational complexity and Mean Square Error(MSE) are presented to evaluate the efficiency of the proposed algorithm.Both analysis and numerical results show that LC-MMSE performs close to the wellknown MMSE estimator with much lower complexity and R-LC-MMSE improves the application of MMSE estimation to specific circumstances.展开更多
Dynamic control of reservoir limited water level is important to reservoir flood control operation.A reasonable limited water level can best utilize flood water resources in addition to flood control.This paper is a t...Dynamic control of reservoir limited water level is important to reservoir flood control operation.A reasonable limited water level can best utilize flood water resources in addition to flood control.This paper is a trial application of the fuzzy information entropy matter-element evaluation method(FIEMEM) as an optimal selection of dynamic control of limited water level.In this method,compound matter elements are established first,followed by establishment of an evaluation model and choice of the optimal scheme on the basis of fuzzy information entropy.In determining weights,a combined weighting method in game theory is adopted to combine experiential weights and mathematical weights so as to eliminate one-sidedness of the single weighting method.Finally,the feasibility of this optimization method is verified by citing dynamic control of Biliuhe reservoir limited water level as an example.展开更多
文摘An improved ant colony optimization （ACO） algorithm is utilized in cell scheduling of the flexible manufaturing process for considering the instrument constraint, manufacturing cost and time. Firstly, the initial weighted directional diagram is set up. Secondly, the algorithm based on the dynamic pheromone updating ensures the quick convergence and the optimal solution, thus improving the feasibility and the stability of the schedule system. Aiming at reducing collaboration with external partners, decreasing the total cost and balancing the production process, the algorithm is efficient in supporting the management process of the manufacturing cell and in strengthening the information arrangement capabitity of the scheduling system. Finally, experimental results of the improved algorithm are compared with those of other algorithms.
基金National Natural Science Foundation of China(No.50575137)National Science and Technology Support Project(No.2006BAF01A44)National High Technology Research and Development Program of China(863 Program,No.2007AA04Z109)
文摘Due to the stubborn nature of dynamic job shop scheduling problem,a novel ant colony coordination mechanism is proposed in this paper to search for an optimal schedule in dynamic environment.In ant colony coordination mechanism,the dynamic job shop is composed of several autonomous ants.These ants coordinate with each other by simulating the ant foraging behavior of spreading pheromone on the trails,by which they can make information available globally,and further more guide ants make optimal decisions.The proposed mechanism is tested by several instances and the results confirm the validity of it.
基金supported by the 2011 China Aerospace Science and Technology Foundationthe Certain Ministry Foundation under Grant No.20212HK03010
文摘Performance of the Adaptive Coding and Modulation(ACM) strongly depends on the retrieved Channel State Information(CSI),which can be obtained using the channel estimation techniques relying on pilot symbol transmission.Earlier analysis of methods of pilot-aided channel estimation for ACM systems were relatively little.In this paper,we investigate the performance of CSI prediction using the Minimum Mean Square Error(MMSE)channel estimator for an ACM system.To solve the two problems of MMSE:high computational operations and oversimplified assumption,we then propose the Low-Complexity schemes(LC-MMSE and Recursion LC-MMSE(R-LC-MMSE)).Computational complexity and Mean Square Error(MSE) are presented to evaluate the efficiency of the proposed algorithm.Both analysis and numerical results show that LC-MMSE performs close to the wellknown MMSE estimator with much lower complexity and R-LC-MMSE improves the application of MMSE estimation to specific circumstances.
基金supported by the Nonprofit Sector Specific Research of Ministry of Water Resources (Grant No. 200701015)
文摘Dynamic control of reservoir limited water level is important to reservoir flood control operation.A reasonable limited water level can best utilize flood water resources in addition to flood control.This paper is a trial application of the fuzzy information entropy matter-element evaluation method(FIEMEM) as an optimal selection of dynamic control of limited water level.In this method,compound matter elements are established first,followed by establishment of an evaluation model and choice of the optimal scheme on the basis of fuzzy information entropy.In determining weights,a combined weighting method in game theory is adopted to combine experiential weights and mathematical weights so as to eliminate one-sidedness of the single weighting method.Finally,the feasibility of this optimization method is verified by citing dynamic control of Biliuhe reservoir limited water level as an example.
