Lot scheduling problem with idle time transfer between processes to minimize mean flow time is very important because to minimize mean flow time is to minimize work in process. But the problem is NP hard and no polyn...Lot scheduling problem with idle time transfer between processes to minimize mean flow time is very important because to minimize mean flow time is to minimize work in process. But the problem is NP hard and no polynomial algorithm exists to guarantee optimal solution. Based the analysis the mathematical structure of the problem, the paper presents a new heuristic algorithm. Computer simulation shows that the proposed heuristic algorithm performs well in terms of both quality of solution and execution speed.展开更多
One of the important steps in mining event sequences is to find frequent episodes. Once the frequent episodes are discovered, rules about temporal relationships can he derived. In this paper, an cfficient algorithm fo...One of the important steps in mining event sequences is to find frequent episodes. Once the frequent episodes are discovered, rules about temporal relationships can he derived. In this paper, an cfficient algorithm for discovering frequent episodes is presented based on the level-wise search algorithm WINEPI. The proposed algorithm gains hetter candidate generation quality by introducing a new Lemma to help to target the combinations of episodes that are interesting in the next level and thins reduces the execution time. Experimental results on artificial and real data show the enhanced efficiency of the algorithm.展开更多
In this article, The genetic algorithm method was proposed, that is, to establish the box structure＇s nonlinear three-dimension optimization numerical model based on thermo-mechanical coupling algorithm, and the obje...In this article, The genetic algorithm method was proposed, that is, to establish the box structure＇s nonlinear three-dimension optimization numerical model based on thermo-mechanical coupling algorithm, and the objective function of welding distortion has been utilized to determine an optimum welding sequence by optimization simulation. The validity of genetic algorithm method combining with the thermo-mechanical nonlinear finite element model is verified by comparison with the experimental data where available. By choosing the appropriate objective function for the considered case, an optimum weldiing.sequence is determined by a genetic algorithm. All done in this study indicates that the new method presented in this article will have important practical application for designing the welding technical parameters in the future.展开更多
Mission planning was thoroughly studied in the areas of multiple intelligent agent systems,such as multiple unmanned air vehicles,and multiple processor systems.However,it still faces challenges due to the system comp...Mission planning was thoroughly studied in the areas of multiple intelligent agent systems,such as multiple unmanned air vehicles,and multiple processor systems.However,it still faces challenges due to the system complexity,the execution order constraints,and the dynamic environment uncertainty.To address it,a coordinated dynamic mission planning scheme is proposed utilizing the method of the weighted AND/OR tree and the AOE-Network.In the scheme,the mission is decomposed into a time-constraint weighted AND/OR tree,which is converted into an AOE-Network for mission planning.Then,a dynamic planning algorithm is designed which uses task subcontracting and dynamic re-decomposition to coordinate conflicts.The scheme can reduce the task complexity and its execution time by implementing real-time dynamic re-planning.The simulation proves the effectiveness of this approach.展开更多
文摘Lot scheduling problem with idle time transfer between processes to minimize mean flow time is very important because to minimize mean flow time is to minimize work in process. But the problem is NP hard and no polynomial algorithm exists to guarantee optimal solution. Based the analysis the mathematical structure of the problem, the paper presents a new heuristic algorithm. Computer simulation shows that the proposed heuristic algorithm performs well in terms of both quality of solution and execution speed.
文摘One of the important steps in mining event sequences is to find frequent episodes. Once the frequent episodes are discovered, rules about temporal relationships can he derived. In this paper, an cfficient algorithm for discovering frequent episodes is presented based on the level-wise search algorithm WINEPI. The proposed algorithm gains hetter candidate generation quality by introducing a new Lemma to help to target the combinations of episodes that are interesting in the next level and thins reduces the execution time. Experimental results on artificial and real data show the enhanced efficiency of the algorithm.
文摘In this article, The genetic algorithm method was proposed, that is, to establish the box structure＇s nonlinear three-dimension optimization numerical model based on thermo-mechanical coupling algorithm, and the objective function of welding distortion has been utilized to determine an optimum welding sequence by optimization simulation. The validity of genetic algorithm method combining with the thermo-mechanical nonlinear finite element model is verified by comparison with the experimental data where available. By choosing the appropriate objective function for the considered case, an optimum weldiing.sequence is determined by a genetic algorithm. All done in this study indicates that the new method presented in this article will have important practical application for designing the welding technical parameters in the future.
基金Projects(61071096,61003233,61073103)supported by the National Natural Science Foundation of ChinaProjects(20100162110012,20110162110042)supported by the Research Fund for the Doctoral Program of Higher Education of China
文摘Mission planning was thoroughly studied in the areas of multiple intelligent agent systems,such as multiple unmanned air vehicles,and multiple processor systems.However,it still faces challenges due to the system complexity,the execution order constraints,and the dynamic environment uncertainty.To address it,a coordinated dynamic mission planning scheme is proposed utilizing the method of the weighted AND/OR tree and the AOE-Network.In the scheme,the mission is decomposed into a time-constraint weighted AND/OR tree,which is converted into an AOE-Network for mission planning.Then,a dynamic planning algorithm is designed which uses task subcontracting and dynamic re-decomposition to coordinate conflicts.The scheme can reduce the task complexity and its execution time by implementing real-time dynamic re-planning.The simulation proves the effectiveness of this approach.
