A Genetic Algorithm-Ant Colony Algorithm(GA-ACA),which can be used to optimize multi-Unit Under Test(UUT)parallel test tasks sequences and resources configuration quickly and accurately,is proposed in the paper.With t...A Genetic Algorithm-Ant Colony Algorithm(GA-ACA),which can be used to optimize multi-Unit Under Test(UUT)parallel test tasks sequences and resources configuration quickly and accurately,is proposed in the paper.With the establishment of the mathematic model of multi-UUT parallel test tasks and resources,the condition of multi-UUT resources mergence is analyzed to obtain minimum resource requirement under minimum test time.The definition of cost efficiency is put forward,followed by the design of gene coding and path selection project,which can satisfy multi-UUT parallel test tasks scheduling.At the threshold of the algorithm,GA is adopted to provide initial pheromone for ACA,and then dual-convergence pheromone feedback mode is applied in ACA to avoid local optimization and parameters dependence.The practical application proves that the algorithm has a remarkable effect on solving the problems of multi-UUT parallel test tasks scheduling and resources configuration.展开更多
To obtain accurate search results and advocate the use of human effort in discovering knowledge, we propose a method based on Ant Colony Algorithm （ACA）. The proposed method simulates the behavior of ants searching ...To obtain accurate search results and advocate the use of human effort in discovering knowledge, we propose a method based on Ant Colony Algorithm （ACA）. The proposed method simulates the behavior of ants searching for food. Specific features such as the behavior of ants searching for food, their established search paths, and the ant ＂neighborhood＂ profile are investigated. The investigation results reveal that the behavior of people searching for useful information resembles that of ants searching for food. We also use semantic annotation and the decreasing matrix dimension approach to accelerate the food searching process an.d shorten the distance between the query starting points and the ultimate answers. A user behavior model is constructed based on personal and domain ontologies. Experimental evaluation with the enhanced ACA has two parts： （1） estimating the efficiency of information retrieval with user interests considered and （2） identifying how to weigh usage and rate user data during recommendation.展开更多
基金supported by“11th Five-year Projects”pre-research projects fund of the National Arming Department
文摘A Genetic Algorithm-Ant Colony Algorithm(GA-ACA),which can be used to optimize multi-Unit Under Test(UUT)parallel test tasks sequences and resources configuration quickly and accurately,is proposed in the paper.With the establishment of the mathematic model of multi-UUT parallel test tasks and resources,the condition of multi-UUT resources mergence is analyzed to obtain minimum resource requirement under minimum test time.The definition of cost efficiency is put forward,followed by the design of gene coding and path selection project,which can satisfy multi-UUT parallel test tasks scheduling.At the threshold of the algorithm,GA is adopted to provide initial pheromone for ACA,and then dual-convergence pheromone feedback mode is applied in ACA to avoid local optimization and parameters dependence.The practical application proves that the algorithm has a remarkable effect on solving the problems of multi-UUT parallel test tasks scheduling and resources configuration.
文摘To obtain accurate search results and advocate the use of human effort in discovering knowledge, we propose a method based on Ant Colony Algorithm （ACA）. The proposed method simulates the behavior of ants searching for food. Specific features such as the behavior of ants searching for food, their established search paths, and the ant ＂neighborhood＂ profile are investigated. The investigation results reveal that the behavior of people searching for useful information resembles that of ants searching for food. We also use semantic annotation and the decreasing matrix dimension approach to accelerate the food searching process an.d shorten the distance between the query starting points and the ultimate answers. A user behavior model is constructed based on personal and domain ontologies. Experimental evaluation with the enhanced ACA has two parts： （1） estimating the efficiency of information retrieval with user interests considered and （2） identifying how to weigh usage and rate user data during recommendation.
