This paper solves Split Demand Vehicle Routing Problem with minimal vehicles and controlled task splits. Our algorithm encodes the mapping between task splits and vehicles into a binary matrix and uses geneticquantum...
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ISBN:
(纸本)9781728183923
This paper solves Split Demand Vehicle Routing Problem with minimal vehicles and controlled task splits. Our algorithm encodes the mapping between task splits and vehicles into a binary matrix and uses genetic quantum algorithm to control the evolvement process. To convert the binary matrix solution into task loading schemes, we design a novel cost function and successfully convert task assignment problem to Transportation Problem which can be solved by Transportation Simplex Method. Our algorithm uses a simple nearest-neighborhood based heuristic to generate vehicle routes and adopts a local search method tailored for SDVRP to improve solution quality. The experimental results show that our algorithm splits few tasks and can obtain many solutions better than CVRP best-known in TSPLIB 95. Further analysis reveals that savings of SDVRP mostly come from CVRP's failure to combine tasks geographically close into one route, when the number of vehicles are restricted to minimum.
Flood susceptibility mapping is an important method for flood research. In this paper, we combine a backpropagation neural network (BPNN) with a genetic quantum algorithm (GQA) for the first time to develop flood susc...
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Flood susceptibility mapping is an important method for flood research. In this paper, we combine a backpropagation neural network (BPNN) with a genetic quantum algorithm (GQA) for the first time to develop flood susceptibility mapping. The area on the Chinese side of the Tumen River Basin was selected as the research object. A set of flood conditioning factors was selected based on relevant literature and an actual situation and then validated using the chi-square test and correlation analysis. Different weights were assigned using stepwise weight assessment ratio analysis. Finally, modeling and flood susceptibility mapping using GQA-BPNN. As a reference, the same work was performed with both the pure BPNN and optimized BPNN using a geneticalgorithm (GA). The results show that the area under the curve, root mean squared error, Nash-Sutcliffe coefficient and percentage of bias are significantly better for the GQA-BPNN than for the BPNN and GA-BPNN and that the flood sensitivity maps constructed by the GQA-BPNN have more flood points in high flood sensitivity areas. Therefore, the GQA-BPNN method can be considered an effective method for flood susceptibility mapping.
In this work, we hybridize the genetic quantum algorithm with the Support Vector Machines classifier for gene selection and classification of high dimensional Microarray Data. We named our algorithm GQA(SVM). Its purp...
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In this work, we hybridize the genetic quantum algorithm with the Support Vector Machines classifier for gene selection and classification of high dimensional Microarray Data. We named our algorithm GQA(SVM). Its purpose is to identify a small subset of genes that could be used to separate two classes of samples with high accuracy. A comparison of the approach with different methods of literature, in particular GA(SVM) and PSOSVM [2], was realized on six different datasets issued of microarray experiments dealing with cancer (leukemia, breast, colon, ovarian, prostate, and lung) and available on Web. The experiments clearified the very good performances of the method. The first contribution shows that the algorithm GQA(SVM) is able to find genes of interest and improve the classification On a meaningful way. The second important contribution consists in the actual discovery of new and challenging results on datasets used.
作者：
Yong, MaYan, WangColl Sci
Liaoning Fuxin 123000 Peoples R China Liaoning
Coll Elect & Control Engn Huludao 125105 Peoples R China
Wireless body sensor network is employed into the under mine rescue system. The network strategy is designed. The geneticalgorithm is used to multi-objective optimize the network. Simulation result shows that this me...
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ISBN:
(纸本)9781424427239
Wireless body sensor network is employed into the under mine rescue system. The network strategy is designed. The geneticalgorithm is used to multi-objective optimize the network. Simulation result shows that this method can optimize the power management obviously, and then improve the network load balancing.
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