This paper presents an efficient algorithm for optimization of radial distribution systems by a network reconfiguration to balance feeder loads and eliminate overload conditions. The system load-balancing index is use...This paper presents an efficient algorithm for optimization of radial distribution systems by a network reconfiguration to balance feeder loads and eliminate overload conditions. The system load-balancing index is used to determine the loading conditions of the system and maximum system loading capacity. The index value has to be minimum in the optimal network reconfiguration of load balancing. The tabu search algorithm is employed to search for the optimal network reconfiguration. The basic idea behind the search is a move from a current solution to its neighborhood by effectively utilizing a memory to provide an efficient search for optimality. It presents low computational effort and is able to find good quality configurations. Simulation results for a radial 69-bus system. The study results show that the optimal on/off patterns of the switches can be identified to give the best network reconfiguration involving balancing of feeder loads while respecting all the constraints.展开更多
To improve overall equipment efficiency(OEE) of a semiconductor wafer wet-etching system,a heuristic tabu search scheduling algorithm is proposed for the wet-etching process in the paper,with material handling robot c...To improve overall equipment efficiency(OEE) of a semiconductor wafer wet-etching system,a heuristic tabu search scheduling algorithm is proposed for the wet-etching process in the paper,with material handling robot capacity and wafer processing time constraints of the process modules considered.Firstly,scheduling problem domains of the wet-etching system(WES) are assumed and defined,and a non-linear programming model is built to maximize the throughput with no defective wafers.On the basis of the model,a scheduling algorithm based on tabu search is presented in this paper.An improved Nawaz,Enscore,and Ham(NEH) heuristic algorithm is used as the initial feasible solution of the proposed heuristic algorithm.Finally,performances of the proposed algorithm are analyzed and evaluated by simulation experiments.The results indicate that the proposed algorithm is valid and practical to generate satisfied scheduling solutions.展开更多
The system will be to build a complete logistics monitoring system based on WebGIS, using the development technology of the third party map which is popular at present, the client technology Ajax is introduced into th...The system will be to build a complete logistics monitoring system based on WebGIS, using the development technology of the third party map which is popular at present, the client technology Ajax is introduced into the two map development platform based on WebGIS, draw lessons from the mature MapABC map service interface for API programming, establish the optimization model of distribution route with hard time windows, and studies the application of tabu search algorithm to solve the distribution path optimization model. At the same time, t;he system can realize vehicle abnormal alarm, shortest path planning and analysis of statistical query functions, can display the corresponding curves on the map that query be some statistical analysis results or a heat map by the user, get a more intuitive feel and better user experience.展开更多
Rough set theory is an effective method to feature selection, which has recently fascinated many researchers. The essence of rough set approach to feature selection is to find a subset of the original features. It is,...Rough set theory is an effective method to feature selection, which has recently fascinated many researchers. The essence of rough set approach to feature selection is to find a subset of the original features. It is, however, an NP-hard problem finding a minimal subset of the features, and it is necessary to investigate effective and efficient heuristic algorithms. This paper presents a novel rough set approach to feature selection based on scatter search metaheuristic. The proposed method, called scatter search rough set attribute reduction （SSAR）, is illustrated by 13 well known datasets from UCI machine learning repository. The proposed heuristic strategy is compared with typical attribute reduction methods including genetic algorithm, ant colony, simulated annealing, and Tabu search. Computational results demonstrate that our algorithm can provide efficient solution to find a minimal subset of the features and show promising and competitive performance on the considered datasets.展开更多
文摘This paper presents an efficient algorithm for optimization of radial distribution systems by a network reconfiguration to balance feeder loads and eliminate overload conditions. The system load-balancing index is used to determine the loading conditions of the system and maximum system loading capacity. The index value has to be minimum in the optimal network reconfiguration of load balancing. The tabu search algorithm is employed to search for the optimal network reconfiguration. The basic idea behind the search is a move from a current solution to its neighborhood by effectively utilizing a memory to provide an efficient search for optimality. It presents low computational effort and is able to find good quality configurations. Simulation results for a radial 69-bus system. The study results show that the optimal on/off patterns of the switches can be identified to give the best network reconfiguration involving balancing of feeder loads while respecting all the constraints.
基金Supported by the National Natural Science Foundation of China(No.71071115,61273035)
文摘To improve overall equipment efficiency(OEE) of a semiconductor wafer wet-etching system,a heuristic tabu search scheduling algorithm is proposed for the wet-etching process in the paper,with material handling robot capacity and wafer processing time constraints of the process modules considered.Firstly,scheduling problem domains of the wet-etching system(WES) are assumed and defined,and a non-linear programming model is built to maximize the throughput with no defective wafers.On the basis of the model,a scheduling algorithm based on tabu search is presented in this paper.An improved Nawaz,Enscore,and Ham(NEH) heuristic algorithm is used as the initial feasible solution of the proposed heuristic algorithm.Finally,performances of the proposed algorithm are analyzed and evaluated by simulation experiments.The results indicate that the proposed algorithm is valid and practical to generate satisfied scheduling solutions.
文摘The system will be to build a complete logistics monitoring system based on WebGIS, using the development technology of the third party map which is popular at present, the client technology Ajax is introduced into the two map development platform based on WebGIS, draw lessons from the mature MapABC map service interface for API programming, establish the optimization model of distribution route with hard time windows, and studies the application of tabu search algorithm to solve the distribution path optimization model. At the same time, t;he system can realize vehicle abnormal alarm, shortest path planning and analysis of statistical query functions, can display the corresponding curves on the map that query be some statistical analysis results or a heat map by the user, get a more intuitive feel and better user experience.
基金supported by the National Natural Science Foundation of China under Grant Nos.71271202 and 70801058
文摘Rough set theory is an effective method to feature selection, which has recently fascinated many researchers. The essence of rough set approach to feature selection is to find a subset of the original features. It is, however, an NP-hard problem finding a minimal subset of the features, and it is necessary to investigate effective and efficient heuristic algorithms. This paper presents a novel rough set approach to feature selection based on scatter search metaheuristic. The proposed method, called scatter search rough set attribute reduction （SSAR）, is illustrated by 13 well known datasets from UCI machine learning repository. The proposed heuristic strategy is compared with typical attribute reduction methods including genetic algorithm, ant colony, simulated annealing, and Tabu search. Computational results demonstrate that our algorithm can provide efficient solution to find a minimal subset of the features and show promising and competitive performance on the considered datasets.
