An effective discrete artificial bee colony(DABC) algorithm is proposed for the flow shop scheduling problem with intermediate buffers(IBFSP) in order to minimize the maximum completion time(i.e makespan). The effecti...An effective discrete artificial bee colony(DABC) algorithm is proposed for the flow shop scheduling problem with intermediate buffers(IBFSP) in order to minimize the maximum completion time(i.e makespan). The effective combination of the insertion and swap operator is applied to producing neighborhood individual at the employed bee phase. The tournament selection is adopted to avoid falling into local optima, while, the optimized insert operator embeds in onlooker bee phase for further searching the neighborhood solution to enhance the local search ability of algorithm. The tournament selection with size 2 is again applied and a better selected solution will be performed destruction and construction of iterated greedy(IG) algorithm, and then the result replaces the worse one. Simulation results show that our algorithm has a better performance compared with the HDDE and CHS which were proposed recently. It provides the better known solutions for the makespan criterion to flow shop scheduling problem with limited buffers for the Car benchmark by Carlier and Rec benchmark by Reeves. The convergence curves show that the algorithm not only has faster convergence speed but also has better convergence value.展开更多
To develop a better approach for spatial evaluation of drinking water quality, an intelligent evaluation method integrating a geographical information system(GIS) and an ant colony clustering algorithm(ACCA) was used....To develop a better approach for spatial evaluation of drinking water quality, an intelligent evaluation method integrating a geographical information system(GIS) and an ant colony clustering algorithm(ACCA) was used. Drinking water samples from 29 wells in Zhenping County, China, were collected and analyzed. 35 parameters on water quality were selected, such as chloride concentration, sulphate concentration, total hardness, nitrate concentration, fluoride concentration, turbidity, pH, chromium concentration, COD, bacterium amount, total coliforms and color. The best spatial interpolation methods for the 35 parameters were found and selected from all types of interpolation methods in GIS environment according to the minimum cross-validation errors. The ACCA was improved through three strategies, namely mixed distance function, average similitude degree and probability conversion functions. Then, the ACCA was carried out to obtain different water quality grades in the GIS environment. In the end, the result from the ACCA was compared with those from the competitive Hopfield neural network(CHNN) to validate the feasibility and effectiveness of the ACCA according to three evaluation indexes, which are stochastic sampling method, pixel amount and convergence speed. It is shown that the spatial water quality grades obtained from the ACCA were more effective, accurate and intelligent than those obtained from the CHNN.展开更多
The characteristic of geographic information system（GfS） spatial data operation is that query is much more frequent than insertion and deletion, and a new hybrid spatial clustering method used to build R-tree for GI...The characteristic of geographic information system（GfS） spatial data operation is that query is much more frequent than insertion and deletion, and a new hybrid spatial clustering method used to build R-tree for GIS spatial data was proposed in this paper. According to the aggregation of clustering method, R-tree was used to construct rules and specialty of spatial data. HCR-tree was the R-tree built with HCR algorithm. To test the efficiency of HCR algorithm, it was applied not only to the data organization of static R-tree but also to the nodes splitting of dynamic R-tree. The results show that R-tree with HCR has some advantages such as higher searching efficiency, less disk accesses and so on.展开更多
基金Projects(61174040,61104178,61374136) supported by the National Natural Science Foundation of ChinaProject(12JC1403400) supported by Shanghai Commission of Science and Technology,ChinaProject supported by the Fundamental Research Funds for the Central Universities,China
文摘An effective discrete artificial bee colony(DABC) algorithm is proposed for the flow shop scheduling problem with intermediate buffers(IBFSP) in order to minimize the maximum completion time(i.e makespan). The effective combination of the insertion and swap operator is applied to producing neighborhood individual at the employed bee phase. The tournament selection is adopted to avoid falling into local optima, while, the optimized insert operator embeds in onlooker bee phase for further searching the neighborhood solution to enhance the local search ability of algorithm. The tournament selection with size 2 is again applied and a better selected solution will be performed destruction and construction of iterated greedy(IG) algorithm, and then the result replaces the worse one. Simulation results show that our algorithm has a better performance compared with the HDDE and CHS which were proposed recently. It provides the better known solutions for the makespan criterion to flow shop scheduling problem with limited buffers for the Car benchmark by Carlier and Rec benchmark by Reeves. The convergence curves show that the algorithm not only has faster convergence speed but also has better convergence value.
基金Projects(41161020,41261026) supported by the National Natural Science Foundation of ChinaProject(BQD2012013) supported by the Research starting Funds for Imported Talents,Ningxia University,China+1 种基金Project(ZR1209) supported by the Natural Science Funds,Ningxia University,ChinaProject(NGY2013005) supported by the Key Science Project of Colleges and Universities in Ningxia,China
文摘To develop a better approach for spatial evaluation of drinking water quality, an intelligent evaluation method integrating a geographical information system(GIS) and an ant colony clustering algorithm(ACCA) was used. Drinking water samples from 29 wells in Zhenping County, China, were collected and analyzed. 35 parameters on water quality were selected, such as chloride concentration, sulphate concentration, total hardness, nitrate concentration, fluoride concentration, turbidity, pH, chromium concentration, COD, bacterium amount, total coliforms and color. The best spatial interpolation methods for the 35 parameters were found and selected from all types of interpolation methods in GIS environment according to the minimum cross-validation errors. The ACCA was improved through three strategies, namely mixed distance function, average similitude degree and probability conversion functions. Then, the ACCA was carried out to obtain different water quality grades in the GIS environment. In the end, the result from the ACCA was compared with those from the competitive Hopfield neural network(CHNN) to validate the feasibility and effectiveness of the ACCA according to three evaluation indexes, which are stochastic sampling method, pixel amount and convergence speed. It is shown that the spatial water quality grades obtained from the ACCA were more effective, accurate and intelligent than those obtained from the CHNN.
文摘The characteristic of geographic information system（GfS） spatial data operation is that query is much more frequent than insertion and deletion, and a new hybrid spatial clustering method used to build R-tree for GIS spatial data was proposed in this paper. According to the aggregation of clustering method, R-tree was used to construct rules and specialty of spatial data. HCR-tree was the R-tree built with HCR algorithm. To test the efficiency of HCR algorithm, it was applied not only to the data organization of static R-tree but also to the nodes splitting of dynamic R-tree. The results show that R-tree with HCR has some advantages such as higher searching efficiency, less disk accesses and so on.
